Triple

T10048104
Position Surface form Disambiguated ID Type / Status
Subject Koka Reservoir E207668 entity
Predicate hasDam P8736 FINISHED
Object Koka Dam E837738 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: Koka Dam | Statement: [Koka Reservoir, hasDam, Koka Dam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Koka Dam
Context triple: [Koka Reservoir, hasDam, Koka Dam]
  • A. Koka Dam chosen
    Koka Dam is a major hydroelectric and irrigation dam in Ethiopia that creates the Koka Reservoir on the Awash River.
  • B. Ukai Dam
    Ukai Dam is a major multi-purpose reservoir and hydroelectric dam in Gujarat, India, built on the Tapi River for irrigation, power generation, and flood control.
  • C. Shimen Dam
    Shimen Dam is a major concrete gravity dam in northern Taiwan that provides water supply, flood control, and hydroelectric power as part of the Shimen Reservoir system.
  • D. Doma Dam
    Doma Dam is a reservoir and recreational site in Nasarawa State, Nigeria, known for its scenic views, fishing opportunities, and role in supporting local agriculture and water supply.
  • E. Hoheikyo Dam
    Hoheikyo Dam is a concrete arch dam in the mountainous outskirts of Sapporo, Japan, known for its scenic reservoir, autumn foliage, and nearby hot spring resorts.
  • 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_69ca835ad0608190b7c80b292da004f5 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cdcf8cf4f0819084d831e1986790be completed April 2, 2026, 2:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69d29a4064a48190b4fdb6bf3ea5af05 completed April 5, 2026, 5:22 p.m.
Created at: March 30, 2026, 8:56 p.m.