Triple

T33705408
Position Surface form Disambiguated ID Type / Status
Subject Harald Zwart E863575 entity
Predicate notableWork P4 FINISHED
Object One Night at McCool's
One Night at McCool's is a 2001 dark comedy crime film that follows three men whose lives are upended by their entanglement with the same enigmatic woman.
 E2063723 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: One Night at McCool's | Statement: [Harald Zwart, notableWork, One Night at McCool's]
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: One Night at McCool's
Triple: [Harald Zwart, notableWork, One Night at McCool's]
Generated description
One Night at McCool's is a 2001 dark comedy crime film that follows three men whose lives are upended by their entanglement with the same enigmatic woman.

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_69f3498844608190bb8f9b14908d2510 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6fab37f808190b82fe40f3cbe1e9b completed May 3, 2026, 7:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a363ca155708190b082e5c8fba84828 completed June 20, 2026, 7:09 a.m.
NEDg Description generation batch_6a3645cd6ffc8190a83cbf74c3f3a863 completed June 20, 2026, 7:48 a.m.
NED2 Entity disambiguation (via description) batch_6a36464b786881909f4bff7db82b05f2 completed June 20, 2026, 7:50 a.m.
Created at: May 1, 2026, 1:43 a.m.