Triple

T5009190
Position Surface form Disambiguated ID Type / Status
Subject Community College of Beaver County E112572 entity
Predicate city P40 FINISHED
Object Monaca E111195 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: Monaca | Statement: [Community College of Beaver County, city, Monaca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Monaca
Context triple: [Community College of Beaver County, city, Monaca]
  • A. Monaca chosen
    Monaca is a small borough located along the Ohio River in Beaver County, Pennsylvania, known historically for its industrial and riverfront character.
  • B. Steenbock
    Steenbock is a German-origin surname most notably associated with biochemist Harry Steenbock, known for his pioneering work on vitamin D fortification.
  • C. Soda City
    Soda City is a popular nickname for Columbia, South Carolina, reflecting the city's historic association with the soft drink industry and its vibrant local culture.
  • D. Nasonville
    Nasonville is a village and census-designated place in the town of Burrillville in northern Rhode Island.
  • E. Carmel
    Carmel is a biblical place name of Hebrew origin, commonly used as a given name and meaning "vineyard" or "garden."
  • 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_69bd4433d0b08190877e83959ef40d81 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd72eb05f881908d7dc3d7cd07b2ae completed March 20, 2026, 4:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69be9269e72881908ea49a77a83b8958 completed March 21, 2026, 12:43 p.m.
Created at: March 20, 2026, 1:35 p.m.