Triple

T27869099
Position Surface form Disambiguated ID Type / Status
Subject Pervez Musharraf E704441 entity
Predicate notableWork P4 FINISHED
Object In the Line of Fire
In the Line of Fire is the political memoir of former Pakistani president and military ruler Pervez Musharraf, detailing his life, rise to power, and perspective on key national and global events.
 E1790592 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: In the Line of Fire | Statement: [Pervez Musharraf, notableWork, In the Line of Fire]
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: In the Line of Fire
Triple: [Pervez Musharraf, notableWork, In the Line of Fire]
Generated description
In the Line of Fire is the political memoir of former Pakistani president and military ruler Pervez Musharraf, detailing his life, rise to power, and perspective on key national and global events.

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_69ef840f12408190b539d00d79658abf completed April 27, 2026, 3:43 p.m.
NER Named-entity recognition batch_69f6394a0a908190b88187af34f8f20c completed May 2, 2026, 5:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12f7493ae4819093364458855b92d3 completed May 24, 2026, 1:04 p.m.
NEDg Description generation batch_6a12f7d3b7048190ae5778d0d22bfd77 completed May 24, 2026, 1:06 p.m.
NED2 Entity disambiguation (via description) batch_6a12fb9650c08190a7ebdbf509b4176b completed May 24, 2026, 1:22 p.m.
Created at: April 27, 2026, 6:23 p.m.