Triple

T3339997
Position Surface form Disambiguated ID Type / Status
Subject Santiago de Liniers E70234 entity
Predicate birthPlace P1 FINISHED
Object Niort E227001 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: Niort | Statement: [Santiago de Liniers, birthPlace, Niort]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Niort
Context triple: [Santiago de Liniers, birthPlace, Niort]
  • A. Niort chosen
    Niort is a historic city in western France known as an administrative and economic center, particularly for its strong mutual insurance and financial services sector.
  • B. La Rochelle
    La Rochelle is a historic French Atlantic port city that became a major stronghold and refuge for Huguenots during the French Wars of Religion.
  • C. Nantes
    Nantes is a historic port city in western France on the Loire River, known for its maritime heritage, cultural institutions, and vibrant arts scene.
  • D. Labourd
    Labourd is a historic coastal province in the French Basque Country, known for its Basque culture, Atlantic beaches, and towns like Bayonne and Biarritz.
  • E. Rochefort
    Rochefort is a historic French port town on the Atlantic coast known for its naval heritage and maritime museum sites.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ad85a405e48190b6e68de7cf9f319e completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb1bf1f648190993ac8e9dda60983 completed March 8, 2026, 5:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69b595dfe0248190a9a45eca075d6eae completed March 14, 2026, 5:07 p.m.
Created at: March 8, 2026, 3:12 p.m.