Triple

T29300474
Position Surface form Disambiguated ID Type / Status
Subject Kokila E742942 entity
Predicate hasCastMember P2308 FINISHED
Object Mohammad Ali
Mohammad Ali is a Pakistani film actor renowned for his prolific career in Urdu cinema, particularly during the 1960s and 1970s.
E1860939 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: Mohammad Ali | Statement: [Kokila, hasCastMember, Mohammad Ali]
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: Mohammad Ali
Triple: [Kokila, hasCastMember, Mohammad Ali]
Generated description
Mohammad Ali is a Pakistani film actor renowned for his prolific career in Urdu cinema, particularly during the 1960s and 1970s.

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_69f09123ed9881909f351f7541933f5e completed April 28, 2026, 10:51 a.m.
NER Named-entity recognition batch_69f665a2ab44819080b1c5f711c229e4 completed May 2, 2026, 8:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25a85eb42c8190b5bf05c33a4480e2 completed June 7, 2026, 5:20 p.m.
NEDg Description generation batch_6a25ac6034a081909518662153fbe1b3 completed June 7, 2026, 5:37 p.m.
NED2 Entity disambiguation (via description) batch_6a25b1426d488190b7d2a0546ab29f59 completed June 7, 2026, 5:58 p.m.
Created at: April 28, 2026, 1:09 p.m.