Triple

T34370749
Position Surface form Disambiguated ID Type / Status
Subject L’amico Fritz E882145 entity
Predicate basedOnAuthor P2806 FINISHED
Object Alexandre Chatrian
Alexandre Chatrian was a 19th-century French writer best known for his popular regional novels co-authored with Émile Erckmann under the joint name Erckmann-Chatrian.
E2187482 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: Alexandre Chatrian | Statement: [L’amico Fritz, basedOnAuthor, Alexandre Chatrian]
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: Alexandre Chatrian
Triple: [L’amico Fritz, basedOnAuthor, Alexandre Chatrian]
Generated description
Alexandre Chatrian was a 19th-century French writer best known for his popular regional novels co-authored with Émile Erckmann under the joint name Erckmann-Chatrian.

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_69f349bf5d7481908dd5da4cbdf74047 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f7184f93a48190b2524ed09be76f06 completed May 3, 2026, 9:41 a.m.
NED1 Entity disambiguation (via context triple) batch_6a39dbb0e9388190a5f7cef4ca7d8d3a completed June 23, 2026, 1:04 a.m.
NEDg Description generation batch_6a39dfec48e08190b42db43d49767409 completed June 23, 2026, 1:22 a.m.
NED2 Entity disambiguation (via description) batch_6a39e055f3988190a10d812e50672758 completed June 23, 2026, 1:24 a.m.
Created at: May 1, 2026, 1:59 a.m.