Triple

T37211333
Position Surface form Disambiguated ID Type / Status
Subject Never So Few E922310 entity
Predicate authorOfSourceWork P2353 FINISHED
Object Tom T. Chamales
Tom T. Chamales was an American novelist and former soldier best known for his gritty World War II and Korean War–themed fiction.
 E2217407 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: Tom T. Chamales | Statement: [Never So Few, authorOfSourceWork, Tom T. Chamales]
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: Tom T. Chamales
Triple: [Never So Few, authorOfSourceWork, Tom T. Chamales]
Generated description
Tom T. Chamales was an American novelist and former soldier best known for his gritty World War II and Korean War–themed fiction.

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_69f76ea4849481909b4a3073efb0114c completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fb36727afc8190a5a5ef47b12f6eed completed May 6, 2026, 12:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40362509988190b3c6f373ad0129cd completed June 27, 2026, 8:44 p.m.
NEDg Description generation batch_6a40370e29b88190896e161008cb4262 completed June 27, 2026, 8:48 p.m.
NED2 Entity disambiguation (via description) batch_6a4038978d88819094f50792d0db95ee completed June 27, 2026, 8:54 p.m.
Created at: May 3, 2026, 4:15 p.m.