Triple

T28219270
Position Surface form Disambiguated ID Type / Status
Subject Point Marion, Pennsylvania E711403 entity
Predicate hasTransportation P105 FINISHED
Object Pennsylvania Route 166
Pennsylvania Route 166 is a state highway in southwestern Pennsylvania that runs along the Monongahela River, connecting small communities in Fayette County.
E2286344 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: Pennsylvania Route 166 | Statement: [Point Marion, Pennsylvania, hasTransportation, Pennsylvania Route 166]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Pennsylvania Route 166
Triple: [Point Marion, Pennsylvania, hasTransportation, Pennsylvania Route 166]
Generated description
Pennsylvania Route 166 is a state highway in southwestern Pennsylvania that runs along the Monongahela River, connecting small communities in Fayette County.

Provenance (5 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_69efb51cb5288190818c1f63a266af11 completed April 27, 2026, 7:12 p.m.
NER Named-entity recognition batch_69f6434f9f888190bd43fde92cd729fe completed May 2, 2026, 6:32 p.m.
NED1 Entity disambiguation (via context triple) batch_6a46a83b9dd08190b0b570e44dc7e238 completed July 2, 2026, 6:04 p.m.
NEDg Description generation batch_6a46a95ddfc88190a039921b9da821b3 completed July 2, 2026, 6:09 p.m.
NED2 Entity disambiguation (via description) batch_6a46ac1574c481909cfeeb064a3450ff completed July 2, 2026, 6:21 p.m.
Created at: April 27, 2026, 10:45 p.m.