Triple

T15681464
Position Surface form Disambiguated ID Type / Status
Subject Phil Connors E377585 entity
Predicate worksWith P398 FINISHED
Object Larry the cameraman
Larry the cameraman is a supporting character in the film "Groundhog Day," serving as the TV crew’s cameraman who works alongside weatherman Phil Connors.
 E1171480 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: Larry the cameraman | Statement: [Phil Connors, worksWith, Larry the cameraman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Larry the cameraman
Context triple: [Phil Connors, worksWith, Larry the cameraman]
  • A. Bobby Bowfinger
    Bobby Bowfinger is the desperate, low-budget movie producer and director played by Steve Martin in the 1999 comedy film "Bowfinger."
  • B. Lloyd
    Lloyd is an American R&B singer known for his smooth vocals and early-2000s hits like "Southside" and "You."
  • C. Lloyd
    Lloyd is the middle name of William Lloyd Garrison, the prominent 19th-century American abolitionist and social reformer.
  • D. Lloyd
    Lloyd is a masculine given name of Welsh origin meaning "grey" or "grey-haired."
  • E. Mr. Cooger
    Mr. Cooger is a sinister, shape-shifting carnival worker and one of the primary antagonists in Ray Bradbury’s dark fantasy novel "Something Wicked This Way Comes."
  • 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: Larry the cameraman
Triple: [Phil Connors, worksWith, Larry the cameraman]
Generated description
Larry the cameraman is a supporting character in the film "Groundhog Day," serving as the TV crew’s cameraman who works alongside weatherman Phil Connors.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Larry the cameraman
Target entity description: Larry the cameraman is a supporting character in the film "Groundhog Day," serving as the TV crew’s cameraman who works alongside weatherman Phil Connors.
  • A. Bobby Bowfinger
    Bobby Bowfinger is the desperate, low-budget movie producer and director played by Steve Martin in the 1999 comedy film "Bowfinger."
  • B. Lloyd
    Lloyd is an American R&B singer known for his smooth vocals and early-2000s hits like "Southside" and "You."
  • C. Lloyd
    Lloyd is the middle name of William Lloyd Garrison, the prominent 19th-century American abolitionist and social reformer.
  • D. Lloyd
    Lloyd is a masculine given name of Welsh origin meaning "grey" or "grey-haired."
  • E. Mr. Cooger
    Mr. Cooger is a sinister, shape-shifting carnival worker and one of the primary antagonists in Ray Bradbury’s dark fantasy novel "Something Wicked This Way Comes."
  • 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_69d85cd2e28481909d4e975bee20872f completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04f306a1c8190a819541a3cc51f5a completed April 16, 2026, 2:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff6ee2a33c81908fcd120ca670b309 completed May 9, 2026, 5:29 p.m.
NEDg Description generation batch_69ff6fd9c968819098b2552a9deb0445 completed May 9, 2026, 5:33 p.m.
NED2 Entity disambiguation (via description) batch_69ff708d42448190a53b90e00721eaa5 completed May 9, 2026, 5:36 p.m.
Created at: April 10, 2026, 4:16 a.m.