Triple

T24876160
Position Surface form Disambiguated ID Type / Status
Subject DD-448 E622574 entity
Predicate identifies P310 FINISHED
Object USS La Vallette
USS La Vallette was a U.S. Navy Fletcher-class destroyer that served with distinction in the Pacific Theater during World War II.
E1756062 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: USS La Vallette | Statement: [DD-448, identifies, USS La Vallette]
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: USS La Vallette
Triple: [DD-448, identifies, USS La Vallette]
Generated description
USS La Vallette was a U.S. Navy Fletcher-class destroyer that served with distinction in the Pacific Theater during World War II.

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_69e2fac3fdbc81909c2ec49be5743cd9 completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f4231f26e0819090a83bc9a45e3277 completed May 1, 2026, 3:50 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1247c94bc48190af7b969991842c60 completed May 24, 2026, 12:35 a.m.
NEDg Description generation batch_6a12488822208190aab1355ac3efd2a6 completed May 24, 2026, 12:38 a.m.
NED2 Entity disambiguation (via description) batch_6a124935c01c8190b9d6d13c4f50a104 completed May 24, 2026, 12:41 a.m.
Created at: April 18, 2026, 5:24 a.m.