Triple

T32190828
Position Surface form Disambiguated ID Type / Status
Subject The Perfect Murder E822239 entity
Predicate director P255 FINISHED
Object Zafar Hai
Zafar Hai is an Indian film director best known internationally for directing the 1988 English-language thriller "The Perfect Murder," adapted from H.R.F. Keating’s Inspector Ghote novel.
E1994880 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: Zafar Hai | Statement: [The Perfect Murder, director, Zafar Hai]
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: Zafar Hai
Triple: [The Perfect Murder, director, Zafar Hai]
Generated description
Zafar Hai is an Indian film director best known internationally for directing the 1988 English-language thriller "The Perfect Murder," adapted from H.R.F. Keating’s Inspector Ghote novel.

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_69f3490819cc81909bae1f8ce99423c5 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6bacd999081908a22bc7e79c57b97 completed May 3, 2026, 3:02 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2f0be8f28081908226661f2085b22a completed June 14, 2026, 8:15 p.m.
NEDg Description generation batch_6a2f0d243400819094bb3a137a28d65b completed June 14, 2026, 8:20 p.m.
NED2 Entity disambiguation (via description) batch_6a2f0db3ab5c81909697d58fc3becd96 completed June 14, 2026, 8:23 p.m.
Created at: May 1, 2026, 12:35 a.m.