Triple

T27862446
Position Surface form Disambiguated ID Type / Status
Subject The Lives of a Bengal Lancer (1935 film) E704263 entity
Predicate oscarWinningCrewMember P163424 FINISHED
Object Paul Wing
Paul Wing was an American film professional best known for his Academy Award-winning work on the 1935 adventure film "The Lives of a Bengal Lancer."
 E1791270 NE FINISHED

How this triple was built (3 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: Paul Wing | Statement: [The Lives of a Bengal Lancer (1935 film), oscarWinningCrewMember, Paul Wing]
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: Paul Wing
Triple: [The Lives of a Bengal Lancer (1935 film), oscarWinningCrewMember, Paul Wing]
Generated description
Paul Wing was an American film professional best known for his Academy Award-winning work on the 1935 adventure film "The Lives of a Bengal Lancer."
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: oscarWinningCrewMember
Context triple: [The Lives of a Bengal Lancer (1935 film), oscarWinningCrewMember, Paul Wing]
  • A. oscarWinningCrewMember chosen
    Indicates that a crew member was part of the team for a work that won an Oscar (Academy Award).
  • B. producedCrewMember
    Indicates that one entity served as a crew member involved in the creation or production of another entity (such as a film, show, or project).
  • C. academyAwardNomineeDirector
    Indicates that a person served as the director of a film that was nominated for an Academy Award.
  • D. hasCrewMember
    Indicates that an entity includes or employs another entity as a member of its crew.
  • E. supportingActorAwardRecipient
    Indicates that an entity has received an award specifically for a supporting acting role in a performance or production.
  • F. None of above.

Provenance (6 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_69ef840f12408190b539d00d79658abf completed April 27, 2026, 3:43 p.m.
NER Named-entity recognition batch_69f63b317e048190963989b732b25b91 completed May 2, 2026, 5:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12f744f9cc819092afa08e2724e77e completed May 24, 2026, 1:04 p.m.
NEDg Description generation batch_6a12f7ff676c8190aee03de906240938 completed May 24, 2026, 1:07 p.m.
NED2 Entity disambiguation (via description) batch_6a12fb9bdbe881909c9f79d153f151a3 completed May 24, 2026, 1:22 p.m.
PD Predicate disambiguation batch_69f6370ea79c81909b761821ee0fa698 completed May 2, 2026, 5:40 p.m.
Created at: April 27, 2026, 6:18 p.m.