Triple

T12483587
Position Surface form Disambiguated ID Type / Status
Subject Diane Arbus E298374 entity
Predicate familyName P18 FINISHED
Object Arbus
Arbus is the surname of Diane Arbus, the influential American photographer renowned for her intimate portraits of marginalized and unconventional subjects.
 E985708 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: Arbus | Statement: [Diane Arbus, familyName, Arbus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Arbus
Context triple: [Diane Arbus, familyName, Arbus]
  • A. Arbory
    Arbory is a rural parish in the south of the Isle of Man, known for its agricultural landscape and traditional Manx village communities.
  • B. Oreshek
    Oreshek is the historic Russian fortress on Lake Ladoga that later gave rise to the town of Shlisselburg.
  • C. Orzola
    Orzola is a small fishing village and port at the northern tip of Lanzarote in the Canary Islands, known as the main departure point for ferries to the nearby island of La Graciosa.
  • D. Yunaska
    Yunaska is the maiden surname of Lara Trump, who is married to Eric Trump, son of former U.S. President Donald Trump.
  • E. Arbore
    Arbore is a Cushitic language spoken by the Arbore people of southern Ethiopia.
  • 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: Arbus
Triple: [Diane Arbus, familyName, Arbus]
Generated description
Arbus is the surname of Diane Arbus, the influential American photographer renowned for her intimate portraits of marginalized and unconventional subjects.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Arbus
Target entity description: Arbus is the surname of Diane Arbus, the influential American photographer renowned for her intimate portraits of marginalized and unconventional subjects.
  • A. Arbory
    Arbory is a rural parish in the south of the Isle of Man, known for its agricultural landscape and traditional Manx village communities.
  • B. Oreshek
    Oreshek is the historic Russian fortress on Lake Ladoga that later gave rise to the town of Shlisselburg.
  • C. Orzola
    Orzola is a small fishing village and port at the northern tip of Lanzarote in the Canary Islands, known as the main departure point for ferries to the nearby island of La Graciosa.
  • D. Yunaska
    Yunaska is the maiden surname of Lara Trump, who is married to Eric Trump, son of former U.S. President Donald Trump.
  • E. Arbore
    Arbore is a Cushitic language spoken by the Arbore people of southern Ethiopia.
  • 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_69d6ada377208190a36011199a4d8558 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94dcef6548190a6d29375bdabd17d completed April 10, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63f29307c8190b024d889d45ba9f7 completed May 2, 2026, 6:15 p.m.
NEDg Description generation batch_69f6437e88c881909b7f1d55c11b0825 completed May 2, 2026, 6:33 p.m.
NED2 Entity disambiguation (via description) batch_69f644464c0c8190a8d4ea4914d32e7f completed May 2, 2026, 6:36 p.m.
Created at: April 8, 2026, 9:56 p.m.