Triple

T15450798
Position Surface form Disambiguated ID Type / Status
Subject Tamyen language E370143 entity
Predicate associatedWithCity P1481 FINISHED
Object San Jose, California E1776 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: San Jose, California | Statement: [Tamyen language, associatedWithCity, San Jose, California]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Jose, California
Context triple: [Tamyen language, associatedWithCity, San Jose, California]
  • A. San Jose
    San Jose is a municipality in the province of Tarlac in the Central Luzon region of the Philippines, known for its predominantly agricultural economy.
  • B. San Jose
    San Jose is a barangay (village-level administrative division) of the municipality of Ternate in the province of Cavite, Philippines.
  • C. San Jose chosen
    San Jose is a major technology and innovation hub in Silicon Valley and one of the largest cities in Northern California.
  • D. San Jose
    San Jose is the main town on the island of Tinian in the Northern Mariana Islands, serving as its administrative and population center.
  • E. San Jose
    San Jose is a coastal municipality in the Philippine province of Negros Oriental known for its rural communities and proximity to Dumaguete City.
  • 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_69d85a19180081909925012fbf4e62a3 completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03efaf82c81908b464e37ce9c159a completed April 16, 2026, 1:44 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00077201c08190a0c3bb259856d5c9 completed May 10, 2026, 4:20 a.m.
Created at: April 10, 2026, 3:21 a.m.