Triple

T10084104
Position Surface form Disambiguated ID Type / Status
Subject Kelantan River E215175 entity
Predicate flowsThrough P225 FINISHED
Object Pasir Mas E207470 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: Pasir Mas | Statement: [Kelantan River, flowsThrough, Pasir Mas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pasir Mas
Context triple: [Kelantan River, flowsThrough, Pasir Mas]
  • A. Pasir Mas chosen
    Pasir Mas is a town in the Malaysian state of Kelantan, known as a local commercial and transport hub near the border with Thailand.
  • B. Pasir Gudang
    Pasir Gudang is an industrial port city in the state of Johor, Malaysia, known for its heavy industries and maritime activities along the Straits of Johor.
  • C. Bandar Lengeh
    Bandar Lengeh is a coastal city and important maritime port on the Persian Gulf in southern Iran’s Hormozgan Province.
  • D. Jasinga
    Jasinga is a district-level area in West Java, Indonesia, known as one of the administrative regions within Bogor Regency.
  • E. Subang Jaya
    Subang Jaya is a major suburban city in the Klang Valley region of Malaysia, known for its dense residential areas, commercial hubs, and educational institutions.
  • 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_69ca83a1eed081908b2e9580f2ebeea7 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdd044c1ec8190b5b48cdb0584d00c completed April 2, 2026, 2:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2b675f4b08190bd8285f210191b93 completed April 5, 2026, 7:22 p.m.
Created at: March 30, 2026, 9 p.m.