Triple

T14011579
Position Surface form Disambiguated ID Type / Status
Subject Benguet E337091 entity
Predicate contains P35 FINISHED
Object Binga Dam E458921 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: Binga Dam | Statement: [Benguet, contains, Binga Dam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Binga Dam
Context triple: [Benguet, contains, Binga Dam]
  • A. Binga Dam chosen
    Binga Dam is a major hydroelectric dam in the Philippines that harnesses the flow of the Agno River for power generation and water management.
  • B. Masinga Dam
    Masinga Dam is a major hydroelectric and water storage reservoir in Kenya that forms part of the Tana River hydropower cascade.
  • C. Rantembe Dam
    Rantembe Dam is a hydroelectric and irrigation dam in Sri Lanka that forms part of the Mahaweli River development scheme.
  • D. Wyangala Dam
    Wyangala Dam is a major water storage and flood mitigation reservoir in New South Wales, Australia, serving irrigation, water supply, and recreational purposes.
  • E. Bariri Dam
    Bariri Dam is a hydroelectric and river regulation structure located on Brazil’s Tietê River, contributing to regional power generation and water management.
  • 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_69d81c645c5c8190b1fd16a285a1b78a completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2ed5cfd0819085b9c860b119a9de completed April 14, 2026, 12:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcd095ca5081908d7fed82e9ef0252 completed May 7, 2026, 5:49 p.m.
Created at: April 9, 2026, 10:19 p.m.