Triple

T20665371
Position Surface form Disambiguated ID Type / Status
Subject Otsiningo Park E507870 entity
Predicate locatedIn P40 FINISHED
Object Binghamton NE NERFINISHED

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: Binghamton | Statement: [Otsiningo Park, locatedIn, Binghamton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Binghamton
Context triple: [Otsiningo Park, locatedIn, Binghamton]
  • A. Binghamton, New York chosen
    Binghamton, New York is a small city in upstate New York known as a former manufacturing hub and home to Binghamton University, located near the Pennsylvania border in the state's Southern Tier.
  • B. Utica
    Utica was an ancient Phoenician colony in North Africa that became one of the earliest and most important urban centers in the western Mediterranean.
  • C. Utica
    Utica is a small town in Hinds County, Mississippi, known for its rural character and historic Southern setting.
  • D. Utica
    Utica is a small village in LaSalle County, Illinois, known as a gateway to the nearby Starved Rock State Park.
  • E. Oneonta
    Oneonta is a small city in central Alabama that serves as the county seat and primary population center of Blount County.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4c059bc81908ea762cd73ea4424 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6b5c2c6d48190bbfe505cf7d973f9 completed April 20, 2026, 11:24 p.m.
Created at: April 16, 2026, 11:44 a.m.