Triple

T16643333
Position Surface form Disambiguated ID Type / Status
Subject Moreland Hills, Ohio E404399 entity
Predicate adjacentTo P224 FINISHED
Object Orange, Ohio E1196490 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: Orange, Ohio | Statement: [Moreland Hills, Ohio, adjacentTo, Orange, Ohio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orange, Ohio
Context triple: [Moreland Hills, Ohio, adjacentTo, Orange, Ohio]
  • A. Orange, Ohio chosen
    Orange, Ohio is a small suburban village in Cuyahoga County known for its residential character and inclusion in the Greater Cleveland area.
  • B. Sylvania, Ohio
    Sylvania, Ohio is a suburban city near Toledo known for its residential communities, strong school system, and proximity to the Michigan border.
  • C. Ada, Ohio
    Ada, Ohio is a small village in northwest Ohio best known as the home of Ohio Northern University.
  • D. Orange Township, Ohio
    Orange Township, Ohio is a small community in Cuyahoga County best known as the birthplace of U.S. President James A. Garfield.
  • E. Hillsboro, Ohio
    Hillsboro, Ohio is a small city in Highland County known as a regional hub for the surrounding rural communities of southwestern Ohio.
  • 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_69d8838a41f08190b0c3f79c47df5078 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37ad3b12c8190a32e33d9ecff9dae completed April 18, 2026, 12:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0084bd1b648190b6189533dcd7b9ac completed May 10, 2026, 1:14 p.m.
Created at: April 10, 2026, 5:18 a.m.