Triple

T7226144
Position Surface form Disambiguated ID Type / Status
Subject Martins E154782 entity
Predicate sharesEtymologyWith P28322 FINISHED
Object Martinez E28750 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: Martinez | Statement: [Martins, sharesEtymologyWith, Martinez]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Martinez
Context triple: [Martins, sharesEtymologyWith, Martinez]
  • A. Martinez chosen
    Martinez is a common Spanish-origin surname widely borne across the Spanish-speaking world and beyond.
  • B. Martinez, California
    Martinez, California is a historic waterfront city in the San Francisco Bay Area known as the county seat of Contra Costa County and for its role as a regional rail and transportation hub.
  • C. Vallejo
    Vallejo is a waterfront city in the San Francisco Bay Area known for its former Mare Island Naval Shipyard and diverse, working-class community.
  • D. Vallejo
    Vallejo is a metro station in Mexico City that serves passengers on Line 6 of the city’s rapid transit system.
  • E. Santa Mesa
    Santa Mesa is a historic district in Manila, Philippines, known for its role as a key battleground during the early stages of the Philippine–American 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_69c68811dd1c8190ac460bb39e64e1f0 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6e9de21e081908f30700f6211c5ef completed March 27, 2026, 8:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7cc17a3788190842a852fb4b96185 completed March 28, 2026, 12:39 p.m.
Created at: March 27, 2026, 2:54 p.m.