Triple

T27164711
Position Surface form Disambiguated ID Type / Status
Subject Maulana Fazlullah E682750 entity
Predicate fullName P16 FINISHED
Object Fazal Hayat
Fazal Hayat, better known as Maulana Fazlullah, was a Pakistani militant leader who headed the Tehrik-i-Taliban Pakistan and gained notoriety for his extremist activities in the Swat Valley.
E1800451 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: Fazal Hayat | Statement: [Maulana Fazlullah, fullName, Fazal Hayat]
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: Fazal Hayat
Triple: [Maulana Fazlullah, fullName, Fazal Hayat]
Generated description
Fazal Hayat, better known as Maulana Fazlullah, was a Pakistani militant leader who headed the Tehrik-i-Taliban Pakistan and gained notoriety for his extremist activities in the Swat Valley.

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_69eefacf6e788190a75a64399d9e3109 completed April 27, 2026, 5:57 a.m.
NER Named-entity recognition batch_69f62541e49c8190ae9f30f48a30f814 completed May 2, 2026, 4:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15b86b25088190ad6082499161f25e completed May 26, 2026, 3:12 p.m.
NEDg Description generation batch_6a15bc3f71b881909b2add9409d75b78 completed May 26, 2026, 3:29 p.m.
NED2 Entity disambiguation (via description) batch_6a15bcf711148190882bb2f6f46fd40e completed May 26, 2026, 3:32 p.m.
Created at: April 27, 2026, 9:20 a.m.