Triple

T21219536
Position Surface form Disambiguated ID Type / Status
Subject The Taking of Pelham 123 (2009 film) E522926 entity
Predicate character P662 FINISHED
Object Walter Garber
Walter Garber is the New York City subway dispatcher portrayed by Denzel Washington in the 2009 thriller "The Taking of Pelham 123," who becomes the primary negotiator during a train hijacking.
E1689464 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: Walter Garber | Statement: [The Taking of Pelham 123 (2009 film), character, Walter Garber]
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: Walter Garber
Triple: [The Taking of Pelham 123 (2009 film), character, Walter Garber]
Generated description
Walter Garber is the New York City subway dispatcher portrayed by Denzel Washington in the 2009 thriller "The Taking of Pelham 123," who becomes the primary negotiator during a train hijacking.

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_69e0b511ed84819099b449b4a111085c completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e73476d93481909c6c99dcc0b16123 completed April 21, 2026, 8:25 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10c0fa870c81909ae631e459d1737f completed May 22, 2026, 8:47 p.m.
NEDg Description generation batch_6a10c2d522988190bc01978dc5ef272f completed May 22, 2026, 8:55 p.m.
NED2 Entity disambiguation (via description) batch_6a10c36b20a0819084d94066362937ee completed May 22, 2026, 8:58 p.m.
Created at: April 16, 2026, 3:43 p.m.