Triple

T32881322
Position Surface form Disambiguated ID Type / Status
Subject Frank Richards E841071 entity
Predicate notableWork P4 FINISHED
Object Old Soldiers Never Die
Old Soldiers Never Die is a classic memoir by British soldier Frank Richards recounting his experiences as a rank-and-file infantryman during World War I.
 E2028360 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: Old Soldiers Never Die | Statement: [Frank Richards, notableWork, Old Soldiers Never Die]
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: Old Soldiers Never Die
Triple: [Frank Richards, notableWork, Old Soldiers Never Die]
Generated description
Old Soldiers Never Die is a classic memoir by British soldier Frank Richards recounting his experiences as a rank-and-file infantryman during World War I.

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_69f349446e288190a70c05bcc4d81172 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6cff18d9c819085107b781e0611c5 completed May 3, 2026, 4:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34c68154e08190844064bd8ef38b89 completed June 19, 2026, 4:33 a.m.
NEDg Description generation batch_6a34c86efa2c8190b6d9daef72581dcd completed June 19, 2026, 4:41 a.m.
NED2 Entity disambiguation (via description) batch_6a34c9336fc4819092f2682493a94cfe completed June 19, 2026, 4:44 a.m.
Created at: May 1, 2026, 1:18 a.m.