Triple

T36043026
Position Surface form Disambiguated ID Type / Status
Subject Murdered by My Father E1042592 entity
Predicate castMember P1668 FINISHED
Object Asheq Akhtar
Asheq Akhtar is an actor known for his role in the British television drama "Murdered by My Father."
E2169527 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: Asheq Akhtar | Statement: [Murdered by My Father, castMember, Asheq Akhtar]
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: Asheq Akhtar
Triple: [Murdered by My Father, castMember, Asheq Akhtar]
Generated description
Asheq Akhtar is an actor known for his role in the British television drama "Murdered by My Father."

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_69f76e2d7e8c8190bac4e90734566799 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7b1c1fc708190b9238de53a28b189 completed May 3, 2026, 8:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38ddf444e08190ba584a4c238e4d30 completed June 22, 2026, 7:02 a.m.
NEDg Description generation batch_6a38f72872308190bdca62b0f482cc66 completed June 22, 2026, 8:49 a.m.
NED2 Entity disambiguation (via description) batch_6a38f890a0788190a15afe7a7e1f7345 completed June 22, 2026, 8:55 a.m.
Created at: May 3, 2026, 4:07 p.m.