Triple

T10961921
Position Surface form Disambiguated ID Type / Status
Subject Port of Seville E258995 entity
Predicate serves P98 FINISHED
Object city of Seville E21819 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: city of Seville | Statement: [Port of Seville, serves, city of Seville]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Seville
Context triple: [Port of Seville, serves, city of Seville]
  • A. Seville, Spain chosen
    Seville, Spain is a historic Andalusian city renowned for its Moorish-influenced architecture, vibrant flamenco culture, and landmarks such as the Seville Cathedral and the Alcázar.
  • B. Seville
    Seville is a historic Spanish city in Andalusia renowned for its rich Moorish and Christian heritage, iconic landmarks like the Giralda and Alcázar, and vibrant cultural traditions such as flamenco.
  • C. Seville
    Seville is a small unincorporated rural community located in Volusia County, Florida, known for its agricultural surroundings and historic character.
  • D. Sevilla
    Sevilla is a station on Madrid's Metro network, serving Line 2 in the city center.
  • E. Sevilla
    Sevilla is a Mexico City Metro station on Line 1, located in the central area of the city and serving nearby commercial and residential zones.
  • 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_69d6aa88500c819097d7032ca578e74f completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7712bf65c8190b847784d885876fd completed April 9, 2026, 9:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69e3449113f08190b83ffbf1b4c46518 completed April 18, 2026, 8:45 a.m.
Created at: April 8, 2026, 9:23 p.m.