Triple

T12647507
Position Surface form Disambiguated ID Type / Status
Subject Shenango River E302066 entity
Predicate flowsThroughSettlement P9749 FINISHED
Object Farrell, Pennsylvania E640974 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: Farrell, Pennsylvania | Statement: [Shenango River, flowsThroughSettlement, Farrell, Pennsylvania]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Farrell, Pennsylvania
Context triple: [Shenango River, flowsThroughSettlement, Farrell, Pennsylvania]
  • A. Farrell, Pennsylvania chosen
    Farrell, Pennsylvania is a small industrial city in western Pennsylvania known for its steel manufacturing history and location within the Shenango Valley.
  • B. Ruffsdale, Pennsylvania
    Ruffsdale, Pennsylvania is a small unincorporated community located in Westmoreland County in the southwestern part of the state.
  • C. Lucerne, Pennsylvania
    Lucerne, Pennsylvania is a small unincorporated community located within the Ligonier Valley region of Pennsylvania.
  • D. Brownsville, Pennsylvania
    Brownsville, Pennsylvania is a historic borough along the Monongahela River known for its early role in American westward expansion and riverboat commerce.
  • E. Mount Pleasant, Pennsylvania
    Mount Pleasant, Pennsylvania is a small borough in Westmoreland County known historically for its coal mining and glass manufacturing industries.
  • 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_69d7bdec9f9c8190b4bac675b7588211 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9614cefdc81908cfc4a4d04aa6eda completed April 10, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6687bbb408190b80da2d0310f82c5 completed May 2, 2026, 9:11 p.m.
Created at: April 9, 2026, 5:17 p.m.