Triple

T2180747
Position Surface form Disambiguated ID Type / Status
Subject Centre-Val de Loire E49035 entity
Predicate containsDepartment P1467 FINISHED
Object Indre
Indre is a rural department in central France known for its quiet countryside, historic towns, and location within the Centre-Val de Loire region.
 E241347 NE FINISHED

How this triple was built (4 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: Indre | Statement: [Centre-Val de Loire, containsDepartment, Indre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Indre
Context triple: [Centre-Val de Loire, containsDepartment, Indre]
  • A. Indre
    Indre is a river in central France that flows through the regions of Berry and Touraine before joining the Loire.
  • B. Innlandet
    Innlandet is a county in eastern Norway known for its inland landscapes, including mountains, forests, and important winter sports venues.
  • C. Vestre
    Vestre is a Norwegian surname most notably associated with Jan Christian Vestre, a prominent Norwegian politician and businessman.
  • D. Emmen
    Emmen is a major town and economic center in the northeastern Netherlands, known for its modern urban layout and attractions such as the Wildlands Adventure Zoo.
  • E. Svaneke
    Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Indre
Triple: [Centre-Val de Loire, containsDepartment, Indre]
Generated description
Indre is a rural department in central France known for its quiet countryside, historic towns, and location within the Centre-Val de Loire region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Indre
Target entity description: Indre is a rural department in central France known for its quiet countryside, historic towns, and location within the Centre-Val de Loire region.
  • A. Indre
    Indre is a river in central France that flows through the regions of Berry and Touraine before joining the Loire.
  • B. Innlandet
    Innlandet is a county in eastern Norway known for its inland landscapes, including mountains, forests, and important winter sports venues.
  • C. Vestre
    Vestre is a Norwegian surname most notably associated with Jan Christian Vestre, a prominent Norwegian politician and businessman.
  • D. Emmen
    Emmen is a major town and economic center in the northeastern Netherlands, known for its modern urban layout and attractions such as the Wildlands Adventure Zoo.
  • E. Svaneke
    Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
  • F. None of above. chosen

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_69a88aa72d348190a9544bb5b8a4e71d completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abbef0e2f0819080ca457fe3b8b419 completed March 7, 2026, 6 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae5da5930c819087e71a609f76e269 completed March 9, 2026, 5:41 a.m.
NEDg Description generation batch_69ae5e4a45a08190bd96af6cda06ab35 completed March 9, 2026, 5:44 a.m.
NED2 Entity disambiguation (via description) batch_69ae5ec4a35c8190bffc7a183497e764 completed March 9, 2026, 5:46 a.m.
Created at: March 4, 2026, 7:45 p.m.