Triple

T22730179
Position Surface form Disambiguated ID Type / Status
Subject Battle of Vauchamps E562112 entity
Predicate location P40 FINISHED
Object Vauchamps
Vauchamps is a commune in northeastern France notable as the site of a significant Napoleonic victory during the 1814 campaign.
E1650164 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: Vauchamps | Statement: [Battle of Vauchamps, location, Vauchamps]
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: Vauchamps
Triple: [Battle of Vauchamps, location, Vauchamps]
Generated description
Vauchamps is a commune in northeastern France notable as the site of a significant Napoleonic victory during the 1814 campaign.

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_69e24550859c81908727d91efc3a81b4 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1792cb9cc8190a7c45032427bca1a completed April 29, 2026, 3:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a101bc2eb5c81909d04175cedf584ad completed May 22, 2026, 9:02 a.m.
NEDg Description generation batch_6a1024c2ab90819085e42e42b48905ce completed May 22, 2026, 9:41 a.m.
NED2 Entity disambiguation (via description) batch_6a10252c2cf48190a31fd50058a5b288 completed May 22, 2026, 9:43 a.m.
Created at: April 17, 2026, 3:21 p.m.