Triple

T11357807
Position Surface form Disambiguated ID Type / Status
Subject Barker Dam area E269006 entity
Predicate hasPart P35 FINISHED
Object Barker Dam E269626 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: Barker Dam | Statement: [Barker Dam area, hasPart, Barker Dam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Barker Dam
Context triple: [Barker Dam area, hasPart, Barker Dam]
  • A. Barker Dam chosen
    Barker Dam is a historic water reservoir and popular scenic spot located within Joshua Tree National Park in California.
  • B. Bartlett Dam
    Bartlett Dam is a concrete multiple-arch dam in central Arizona that creates Bartlett Lake, providing water storage, flood control, and recreation on the Verde River.
  • C. Barkley Dam
    Barkley Dam is a major hydroelectric and flood-control dam in western Kentucky that helps form Lake Barkley and supports navigation, power generation, and recreation in the region.
  • D. Brantley Dam
    Brantley Dam is a major flood-control and irrigation reservoir structure on the Pecos River in southeastern New Mexico.
  • E. Parker Dam
    Parker Dam is a concrete arch-gravity dam on the Colorado River best known for creating Lake Havasu and supplying water and hydroelectric power to parts of California and Arizona.
  • 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_69d6aacbe18081909e5fadb50082dd96 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7ea419afc8190b3a93141d015ebdf completed April 9, 2026, 6:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60a4f804c81909abf5e9a88da1d91 completed May 2, 2026, 2:29 p.m.
Created at: April 8, 2026, 9:33 p.m.