Triple

T31071017
Position Surface form Disambiguated ID Type / Status
Subject 99 River Street E791816 entity
Predicate character P662 FINISHED
Object Ernie Driscoll
Ernie Driscoll is the embittered ex-boxer protagonist of the 1953 film noir "99 River Street," whose life unravels amid crime, betrayal, and a desperate struggle for redemption.
 E1973467 NE FINISHED

How this triple was built (2 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: Ernie Driscoll | Statement: [99 River Street, character, Ernie Driscoll]
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: Ernie Driscoll
Triple: [99 River Street, character, Ernie Driscoll]
Generated description
Ernie Driscoll is the embittered ex-boxer protagonist of the 1953 film noir "99 River Street," whose life unravels amid crime, betrayal, and a desperate struggle for redemption.

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_69f224ccdbbc81909b0cdb4cc2d70c7a completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f695b566388190a0e6018bf397aa67 completed May 3, 2026, 12:24 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b8493e1b88190ac18f5ace044832b completed June 12, 2026, 4:01 a.m.
NEDg Description generation batch_6a2b8590d4f48190b126ede3e93631b9 completed June 12, 2026, 4:05 a.m.
NED2 Entity disambiguation (via description) batch_6a2b85fe65348190801652c66bb72cf9 completed June 12, 2026, 4:07 a.m.
Created at: April 29, 2026, 9:01 p.m.