Triple

T19722363
Position Surface form Disambiguated ID Type / Status
Subject Hasdai Crescas E473641 entity
Predicate workLocation P7 FINISHED
Object Saragossa NE NERFINISHED

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: Saragossa | Statement: [Hasdai Crescas, workLocation, Saragossa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saragossa
Context triple: [Hasdai Crescas, workLocation, Saragossa]
  • A. Zaragosa
    Zaragosa is a barangay (village-level administrative division) within the municipality of Badian in the province of Cebu, Philippines.
  • 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 municipality in the La Libertad Department of El Salvador, known for its growing suburban communities near the capital, San Salvador.
  • D. 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.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e517ebd48190979ee76723bcfadf completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e649f587d88190bf519fec7ce634d3 completed April 20, 2026, 3:44 p.m.
Created at: April 10, 2026, 1:46 p.m.