Triple

T2877433
Position Surface form Disambiguated ID Type / Status
Subject Guimaras E56910 entity
Predicate hasMunicipality P847 FINISHED
Object Jordan E237971 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: Jordan | Statement: [Guimaras, hasMunicipality, Jordan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jordan
Context triple: [Guimaras, hasMunicipality, Jordan]
  • A. Jordan chosen
    Jordan is a municipality in the Philippines that serves as the capital of the island province of Guimaras in the Western Visayas region.
  • B. Jordan
    Jordan is a Middle Eastern country located at the crossroads of Asia, Africa, and Europe, known for its ancient archaeological sites like Petra and its strategic political role in the region.
  • C. Jordan
    Jordan is a popular Nike-owned athletic footwear and apparel brand originally inspired by basketball legend Michael Jordan and known for its iconic Air Jordan sneakers.
  • D. Jordan
    Jordan is a common given name used by people of all genders in many English-speaking and other countries.
  • E. Madyan
    Madyan is a scenic hill town and tourist resort in Pakistan’s Swat Valley, known for its cool climate, river views, and surrounding mountains.
  • 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_69ab4a4ced288190ab6d3e062d10f7f6 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abe007329c8190b0bc1851c7307124 completed March 7, 2026, 8:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69b08648923c8190bd544177b825a494 completed March 10, 2026, 8:59 p.m.
Created at: March 6, 2026, 10:03 p.m.