Triple

T10760411
Position Surface form Disambiguated ID Type / Status
Subject Saitama (city) E253810 entity
Predicate twinTown P1072 FINISHED
Object Zaragoza 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 | Statement: [Saitama (city), twinTown, Zaragoza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zaragoza
Context triple: [Saitama (city), twinTown, Zaragoza]
  • A. 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.
  • B. 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.
  • C. 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.
  • D. Burgos
    Burgos is a small coastal municipality on the northern tip of Siargao Island in the Philippines, known for its quiet beaches and surf spots.
  • E. Burgos
    Burgos is a historic city in northern Spain known for its medieval architecture and its prominent role during the Spanish Civil War.
  • 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_69d6aa5f54f4819082d0bbcb6f8797e6 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d731a14c7481909c6f4f9b15dc130f completed April 9, 2026, 4:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69de225f57948190aaf2954bce91f752 completed April 14, 2026, 11:17 a.m.
Created at: April 8, 2026, 9:16 p.m.