Triple

T4719976
Position Surface form Disambiguated ID Type / Status
Subject Negros Island E104739 entity
Predicate hasCity P316 FINISHED
Object Tanjay E251854 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: Tanjay | Statement: [Negros Island, hasCity, Tanjay]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tanjay
Context triple: [Negros Island, hasCity, Tanjay]
  • A. Tanjay chosen
    Tanjay is a component city in the province of Negros Oriental in the Philippines, known for its agricultural economy and cultural festivals.
  • B. Maljamar
    Maljamar is a small unincorporated community in southeastern New Mexico known historically for its oil and gas activity.
  • C. Kapyong
    Kapyong is a Korean War battlefield in South Korea renowned for a pivotal 1951 engagement in which outnumbered UN forces, including Canadian troops, halted a major Chinese offensive.
  • D. Tagbanwa
    Tagbanwa is an indigenous Philippine script historically used by the Tagbanwa people of Palawan for writing their Austronesian language.
  • E. Agulo
    Agulo is a small, picturesque coastal village and municipality on the island of La Gomera in Spain’s Canary Islands, known for its traditional architecture and dramatic cliffside scenery.
  • 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_69bd43ec4a348190bc41afae43375e71 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6428e9e081908ce4041183cad13b completed March 20, 2026, 3:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69be108fe3b08190b3d306ca4b39860d completed March 21, 2026, 3:29 a.m.
Created at: March 20, 2026, 1:18 p.m.