Triple

T14325671
Position Surface form Disambiguated ID Type / Status
Subject Andegavum E355208 entity
Predicate hasAlternativeLatinForm P5923 FINISHED
Object Andegava E355208 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: Andegava | Statement: [Andegavum, hasAlternativeLatinForm, Andegava]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Andegava
Context triple: [Andegavum, hasAlternativeLatinForm, Andegava]
  • A. Andegavum chosen
    Andegavum is the Latin name for the French city of Angers, historically used in Roman and medieval sources.
  • B. Algete
    Algete is a municipality in the Community of Madrid, Spain, located to the north of the capital and characterized by its mix of residential areas and surrounding agricultural land.
  • C. Vaala
    Vaala is a municipality in northern Finland known for its lakeside landscapes and location along the Oulujoki river.
  • D. Andom
    Andom is a surname most notably associated with Aman Andom, an Ethiopian military officer and former head of state.
  • E. Viddalba
    Viddalba is a small town and comune in northern Sardinia, Italy, known for its rural setting and proximity to the Gallura region’s coastal and archaeological attractions.
  • 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_69d8278fa2108190bc0d0e7939c1eb03 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de883e6a288190b6c22f630a1eef3c completed April 14, 2026, 6:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4690a79c819099cc4ae9a10ba0db completed May 8, 2026, 2:12 a.m.
Created at: April 10, 2026, 1:13 a.m.