Triple

T7400446
Position Surface form Disambiguated ID Type / Status
Subject Nagaon district E170732 entity
Predicate borderedBy P224 FINISHED
Object Hojai district E662245 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: Hojai district | Statement: [Nagaon district, borderedBy, Hojai district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hojai district
Context triple: [Nagaon district, borderedBy, Hojai district]
  • A. Hojai chosen
    Hojai is a town in the Indian state of Assam known as a commercial and cultural center, particularly for its role in the region’s trade and local industries.
  • B. Seongju County
    Seongju County is a rural administrative region in southeastern South Korea known for its melon farming and traditional cultural heritage.
  • C. Bonghwa County
    Bonghwa County is a rural administrative region in northeastern South Korea known for its mountainous landscapes, forests, and traditional cultural heritage.
  • D. Ongjin County
    Ongjin County is a rural island and coastal county in South Korea known for its fishing communities, natural scenery, and administrative affiliation with the metropolitan city of Incheon.
  • E. Yeongyang County
    Yeongyang County is a rural administrative region in eastern South Korea known for its mountainous terrain, low population density, and production of specialty agricultural products such as apples and chili peppers.
  • 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_69c68a5f04188190ac266569c9280347 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f24f6b7c81908cb61395239d03a0 completed March 27, 2026, 9:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69c81ed378308190b925941415db596d completed March 28, 2026, 6:32 p.m.
Created at: March 27, 2026, 3:10 p.m.