Triple

T18130635
Position Surface form Disambiguated ID Type / Status
Subject Domenico Fancelli E433999 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: [Domenico Fancelli, workLocation, Saragossa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saragossa
Context triple: [Domenico Fancelli, 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 small municipality and town in the northern Mexican state of Coahuila, known for its rural character and proximity to the U.S. border.
  • 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 barangay (village-level administrative division) within the municipality of Oton in the province of Iloilo, Philippines.
  • 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_69d8b909e8cc81908df4cc2b8ea6d11f completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4ddf1e2508190993f65ca137fdf63 completed April 19, 2026, 1:51 p.m.
Created at: April 10, 2026, 10:29 a.m.