Triple

T15529462
Position Surface form Disambiguated ID Type / Status
Subject Berryville, Texas E370171 entity
Predicate locatedOnWaterbody P1489 FINISHED
Object Lake Palestine E370176 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: Lake Palestine | Statement: [Berryville, Texas, locatedOnWaterbody, Lake Palestine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lake Palestine
Context triple: [Berryville, Texas, locatedOnWaterbody, Lake Palestine]
  • A. Lake Palestine chosen
    Lake Palestine is a large reservoir in East Texas popular for fishing, boating, and lakeside recreation.
  • B. Lake Gilead
    Lake Gilead is a small reservoir in Putnam County, New York, that serves as part of New York City's Croton water supply system.
  • C. Lake Jordan
    Lake Jordan is a man-made reservoir in central Alabama known for recreational boating, fishing, and lakeside residential communities.
  • D. Lake Sai
    Lake Sai is one of the Fuji Five Lakes in Yamanashi Prefecture, Japan, known for its scenic views of Mount Fuji and tranquil natural surroundings.
  • E. Lake Zoar
    Lake Zoar is a man-made reservoir in western Connecticut popular for boating, fishing, and other recreational activities.
  • 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_69d85cc521a08190921fb50319dddc34 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e0414773548190b3311515f9d957dd completed April 16, 2026, 1:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff3d5b989c8190a76612df167ba1dd completed May 9, 2026, 1:57 p.m.
Created at: April 10, 2026, 4:05 a.m.