Triple

T3659016
Position Surface form Disambiguated ID Type / Status
Subject The Fisher King E77603 entity
Predicate character P662 FINISHED
Object Jack Lucas
Jack Lucas is a disgraced, guilt-ridden former shock jock whose search for redemption drives the central narrative of the film "The Fisher King."
 E378396 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: Jack Lucas | Statement: [The Fisher King, character, Jack Lucas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Jack Lucas
Context triple: [The Fisher King, character, Jack Lucas]
  • A. Charlie Lucas
    Charlie Lucas is an actor known for his role in the film "Tea with Mussolini."
  • B. Lance Johnson
    Lance Johnson is a film producer known for his work on the biographical comedy-drama "The Life and Death of Peter Sellers."
  • C. Marc McClure
    Marc McClure is an American actor best known for playing Jimmy Olsen in the Superman film series and Dave McFly in the Back to the Future trilogy.
  • D. Jonathan Lucas
    Jonathan Lucas is a film editor known for his work on the feature film "Troop Zero."
  • E. Henry Lucas
    Henry Lucas was a 17th-century English clergyman, politician, and benefactor whose endowment led to the creation of the prestigious Lucasian Chair of Mathematics at the University of Cambridge.
  • 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: Jack Lucas
Triple: [The Fisher King, character, Jack Lucas]
Generated description
Jack Lucas is a disgraced, guilt-ridden former shock jock whose search for redemption drives the central narrative of the film "The Fisher King."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Jack Lucas
Target entity description: Jack Lucas is a disgraced, guilt-ridden former shock jock whose search for redemption drives the central narrative of the film "The Fisher King."
  • A. Charlie Lucas
    Charlie Lucas is an actor known for his role in the film "Tea with Mussolini."
  • B. Lance Johnson
    Lance Johnson is a film producer known for his work on the biographical comedy-drama "The Life and Death of Peter Sellers."
  • C. Marc McClure
    Marc McClure is an American actor best known for playing Jimmy Olsen in the Superman film series and Dave McFly in the Back to the Future trilogy.
  • D. Jonathan Lucas
    Jonathan Lucas is a film editor known for his work on the feature film "Troop Zero."
  • E. Henry Lucas
    Henry Lucas was a 17th-century English clergyman, politician, and benefactor whose endowment led to the creation of the prestigious Lucasian Chair of Mathematics at the University of Cambridge.
  • 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_69ad85dfc4dc8190a441864202ab2a7a completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc3d48a2081908ac0f76d548a53ee completed March 8, 2026, 6:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b48842b28881908c6a077cfaa8b092 completed March 13, 2026, 9:57 p.m.
NEDg Description generation batch_69b48e0d2cfc8190b55d8060cc092411 completed March 13, 2026, 10:22 p.m.
NED2 Entity disambiguation (via description) batch_69b4b96e73fc8190aa11d1e1a06d5c25 completed March 14, 2026, 1:27 a.m.
Created at: March 8, 2026, 3:25 p.m.