Triple

T14381802
Position Surface form Disambiguated ID Type / Status
Subject Port of Sagunto E356620 entity
Predicate locatedIn P40 FINISHED
Object Sagunto E361624 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: Sagunto | Statement: [Port of Sagunto, locatedIn, Sagunto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sagunto
Context triple: [Port of Sagunto, locatedIn, Sagunto]
  • A. Sagunto chosen
    Sagunto is a historic coastal town in eastern Spain renowned for its ancient Roman theatre and hilltop castle overlooking the Mediterranean.
  • B. Alzira
    Alzira is a historic town and municipality in eastern Spain known for its agricultural heritage and location along the Júcar River in the Valencian Community.
  • C. Gandia
    Gandia is a coastal city in eastern Spain known for its Mediterranean beaches, historical heritage, and role as a tourist destination in the province of Valencia.
  • D. Barbastro
    Barbastro is a historic town in the Aragon region of northeastern Spain, known for its wine production and medieval architecture.
  • E. Tarragona
    Tarragona is a coastal municipality in the province of Davao Oriental on the southeastern island of Mindanao in the Philippines.
  • 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_69d8279163a081908aec45c0e3f1e02f completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de900bbfb08190a1e56f281a2374c0 completed April 14, 2026, 7:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd6d7ed3ec8190b97128733419845b completed May 8, 2026, 4:58 a.m.
Created at: April 10, 2026, 1:16 a.m.