Triple

T6161901
Position Surface form Disambiguated ID Type / Status
Subject Rachel Getting Married E137461 entity
Predicate producer P490 FINISHED
Object Neda Armian
Neda Armian is a film producer best known for her work on acclaimed independent films such as "Rachel Getting Married."
 E574321 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Neda Armian | Statement: [Rachel Getting Married, producer, Neda Armian]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Neda Armian
Context triple: [Rachel Getting Married, producer, Neda Armian]
  • A. Nona Balakian
    Nona Balakian was an influential American literary critic and longtime editor at The New York Times Book Review, known for championing contemporary fiction and criticism.
  • B. Ana Khesarian
    Ana Khesarian is a central fictional character in the 2016 historical drama film "The Promise," which is set during the final years of the Ottoman Empire and the Armenian Genocide.
  • C. Micheline Aharonian Marcom
    Micheline Aharonian Marcom is an American novelist known for her lyrical, experimental fiction that often explores themes of Armenian identity, memory, and the aftermath of genocide.
  • D. Tedi Sarafian
    Tedi Sarafian is an American screenwriter and film producer best known for his work on major action and science fiction films.
  • E. Hedieh Tehrani
    Hedieh Tehrani is a prominent Iranian film actress acclaimed for her intense, nuanced performances in contemporary Iranian cinema.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Neda Armian
Triple: [Rachel Getting Married, producer, Neda Armian]
Generated description
Neda Armian is a film producer best known for her work on acclaimed independent films such as "Rachel Getting Married."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Neda Armian
Target entity description: Neda Armian is a film producer best known for her work on acclaimed independent films such as "Rachel Getting Married."
  • A. Nona Balakian
    Nona Balakian was an influential American literary critic and longtime editor at The New York Times Book Review, known for championing contemporary fiction and criticism.
  • B. Ana Khesarian
    Ana Khesarian is a central fictional character in the 2016 historical drama film "The Promise," which is set during the final years of the Ottoman Empire and the Armenian Genocide.
  • C. Micheline Aharonian Marcom
    Micheline Aharonian Marcom is an American novelist known for her lyrical, experimental fiction that often explores themes of Armenian identity, memory, and the aftermath of genocide.
  • D. Tedi Sarafian
    Tedi Sarafian is an American screenwriter and film producer best known for his work on major action and science fiction films.
  • E. Hedieh Tehrani
    Hedieh Tehrani is a prominent Iranian film actress acclaimed for her intense, nuanced performances in contemporary Iranian cinema.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69c008a54fc88190b6ce4416490ca79d completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c05d371484819090c18b62b095b49e completed March 22, 2026, 9:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c14199f024819089af02b1c0eebfad completed March 23, 2026, 1:35 p.m.
NEDg Description generation batch_69c1467ef4d48190b714823935318c0a completed March 23, 2026, 1:56 p.m.
NED2 Entity disambiguation (via description) batch_69c146f59d9881908fdc6c0137f0ead7 completed March 23, 2026, 1:58 p.m.
Created at: March 22, 2026, 4:17 p.m.