Triple

T14010953
Position Surface form Disambiguated ID Type / Status
Subject Carlos Ezquerra E337076 entity
Predicate placeOfBirth P1 FINISHED
Object Zaragoza, Spain E55920 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: Zaragoza, Spain | Statement: [Carlos Ezquerra, placeOfBirth, Zaragoza, Spain]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zaragoza, Spain
Context triple: [Carlos Ezquerra, placeOfBirth, Zaragoza, Spain]
  • A. Zaragoza
    Zaragoza is a metro station on Mexico City’s Line 1 that serves as a key eastern access point to the city’s rapid transit network.
  • B. Zaragoza chosen
    Zaragoza is a historic city in northeastern Spain, known for landmarks like the Basilica del Pilar and its role as a major cultural and economic center in the Aragon region.
  • C. Zaragoza
    Zaragoza is a barangay (village-level administrative division) within the municipality of Oton in the province of Iloilo, Philippines.
  • D. Zaragoza
    Zaragoza is a small municipality and town in the northern Mexican state of Coahuila, known for its rural character and proximity to the U.S. border.
  • E. Alburquerque, Spain
    Alburquerque, Spain is a historic town in the Extremadura region near the Portuguese border, known for its medieval castle and strategic frontier location.
  • 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_69d81c645c5c8190b1fd16a285a1b78a completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2ed5cfd0819085b9c860b119a9de completed April 14, 2026, 12:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69fbc32b459c81908b652286f444e940 completed May 6, 2026, 10:39 p.m.
Created at: April 9, 2026, 10:19 p.m.