Triple

T12613108
Position Surface form Disambiguated ID Type / Status
Subject The Gangster E301178 entity
Predicate basedOn P98 FINISHED
Object Low Company
Low Company is a crime-themed novel that served as the literary basis for the film "The Gangster."
E993133 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: Low Company | Statement: [The Gangster, basedOn, Low Company]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Low Company
Context triple: [The Gangster, basedOn, Low Company]
  • A. The Hoose-Gow
    The Hoose-Gow is a 1929 Laurel and Hardy short comedy film known for its prison-escape antics and slapstick humor.
  • B. The Honest Toun
    The Honest Toun is the traditional nickname of Musselburgh, a historic coastal town in East Lothian, Scotland, known for its long-standing civic pride and heritage.
  • C. Hullabaloo
    Hullabaloo was a 1960s American musical variety television show that featured popular rock and pop performers of the era.
  • D. Shankman
    Shankman is a surname most notably associated with American film director and choreographer Adam Shankman.
  • E. The Hucksters
    The Hucksters is a 1947 satirical drama film about postwar American advertising, starring Clark Gable and featuring Sydney Greenstreet in a memorable supporting role.
  • 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: Low Company
Triple: [The Gangster, basedOn, Low Company]
Generated description
Low Company is a crime-themed novel that served as the literary basis for the film "The Gangster."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Low Company
Target entity description: Low Company is a crime-themed novel that served as the literary basis for the film "The Gangster."
  • A. The Hoose-Gow
    The Hoose-Gow is a 1929 Laurel and Hardy short comedy film known for its prison-escape antics and slapstick humor.
  • B. The Honest Toun
    The Honest Toun is the traditional nickname of Musselburgh, a historic coastal town in East Lothian, Scotland, known for its long-standing civic pride and heritage.
  • C. Hullabaloo
    Hullabaloo was a 1960s American musical variety television show that featured popular rock and pop performers of the era.
  • D. Shankman
    Shankman is a surname most notably associated with American film director and choreographer Adam Shankman.
  • E. The Hucksters
    The Hucksters is a 1947 satirical drama film about postwar American advertising, starring Clark Gable and featuring Sydney Greenstreet in a memorable supporting role.
  • 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_69d7bdeaf49c8190b13800111fa77ea3 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d960c2e5b88190a7cc16002b218d8a completed April 10, 2026, 8:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69f65ed1044c8190bbe881d32a4bf29e completed May 2, 2026, 8:30 p.m.
NEDg Description generation batch_69f6617479ec819080eac67abc9bc435 completed May 2, 2026, 8:41 p.m.
NED2 Entity disambiguation (via description) batch_69f662695a348190b9911a19dfc9e779 completed May 2, 2026, 8:45 p.m.
Created at: April 9, 2026, 5:12 p.m.