Triple

T3647690
Position Surface form Disambiguated ID Type / Status
Subject Rebecca Hall E77340 entity
Predicate notableWork P4 FINISHED
Object Christine
"Christine" is a 2016 biographical drama film starring Rebecca Hall as troubled 1970s news reporter Christine Chubbuck.
 E375963 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: Christine | Statement: [Rebecca Hall, notableWork, Christine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Christine
Context triple: [Rebecca Hall, notableWork, Christine]
  • A. Christine
    Christine is a feminine given name of Greek origin meaning "follower of Christ," widely used in many Western countries.
  • B. Christine
    Christine is the birth name of Chrissy Teigen, an American model, television personality, and cookbook author.
  • C. Christine
    Christine is the given name of Canadian soccer legend Christine Sinclair, one of the most prolific goal scorers in international football history.
  • D. Christine
    Christine is a character from the Marvel Cinematic Universe film "Iron Man 3," where she appears as the clairvoyant antagonist manipulating events from behind the scenes.
  • E. Christine
    Christine is the protagonist of H. P. Lovecraft’s novel "Love," around whom the story’s emotional and psychological developments revolve.
  • 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: Christine
Triple: [Rebecca Hall, notableWork, Christine]
Generated description
"Christine" is a 2016 biographical drama film starring Rebecca Hall as troubled 1970s news reporter Christine Chubbuck.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Christine
Target entity description: "Christine" is a 2016 biographical drama film starring Rebecca Hall as troubled 1970s news reporter Christine Chubbuck.
  • A. Christine
    Christine is the birth name of Chrissy Teigen, an American model, television personality, and cookbook author.
  • B. Christine
    Christine is the given name of Canadian soccer legend Christine Sinclair, one of the most prolific goal scorers in international football history.
  • C. Christine
    Christine is the protagonist of H. P. Lovecraft’s novel "Love," around whom the story’s emotional and psychological developments revolve.
  • D. Christine
    Christine is a character from the Marvel Cinematic Universe film "Iron Man 3," where she appears as the clairvoyant antagonist manipulating events from behind the scenes.
  • E. Christine
    Christine is a feminine given name of Greek origin meaning "follower of Christ," widely used in many Western countries.
  • 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_69ad85de1b988190a45f8dbfebc806fc completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc38aa2388190bf1af926375e2433 completed March 8, 2026, 6:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69b44f394f9c8190881edc18b544dbb7 completed March 13, 2026, 5:54 p.m.
NEDg Description generation batch_69b45347e364819080c0dac755405462 completed March 13, 2026, 6:11 p.m.
NED2 Entity disambiguation (via description) batch_69b45f4640e881909b0e3b68cb899669 completed March 13, 2026, 7:02 p.m.
Created at: March 8, 2026, 3:24 p.m.