Triple

T17115332
Position Surface form Disambiguated ID Type / Status
Subject Comune of Vedelago E415322 entity
Predicate hasAdministrativeCenter P1474 FINISHED
Object Vedelago E1250873 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: Vedelago | Statement: [Comune of Vedelago, hasAdministrativeCenter, Vedelago]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vedelago
Context triple: [Comune of Vedelago, hasAdministrativeCenter, Vedelago]
  • A. Vedelago chosen
    Vedelago is a municipality in the Veneto region of northern Italy, known for its historic villas and rural landscape.
  • B. Zalambessa
    Zalambessa is a town in the Tigray Region of northern Ethiopia, situated near the border with Eritrea and known for its strategic location along the main road between the two countries.
  • C. Ovindoli
    Ovindoli is a mountain village and ski resort in the Abruzzo region of central Italy, known for its outdoor recreation and scenic Apennine landscapes.
  • D. Yungay
    Yungay is a small Chilean city located in the Ñuble Region, known for its agricultural surroundings and Andean foothill landscapes.
  • E. Yungay
    Yungay is a town in north-central Peru known for being devastated by a catastrophic earthquake and landslide in 1970, after which a new settlement was built nearby.
  • 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_69d886d090cc8190a39cb94992586905 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3e80528588190a877dcc6d6d3a392 completed April 18, 2026, 8:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a014145f7988190803d5c5e4f2705b0 completed May 11, 2026, 2:39 a.m.
Created at: April 10, 2026, 5:35 a.m.