Triple

T30365043
Position Surface form Disambiguated ID Type / Status
Subject Pennsylvania Route 954 E772395 entity
Predicate hasJunctionWith P1018 FINISHED
Object Pennsylvania Route 110
Pennsylvania Route 110 is a state highway in Pennsylvania that serves as a connector route in the western part of the state, linking local communities and intersecting with several regional roads.
E2288133 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 110 | Statement: [Pennsylvania Route 954, hasJunctionWith, Pennsylvania Route 110]
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 110
Triple: [Pennsylvania Route 954, hasJunctionWith, Pennsylvania Route 110]
Generated description
Pennsylvania Route 110 is a state highway in Pennsylvania that serves as a connector route in the western part of the state, linking local communities and intersecting with several regional roads.

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_69f2248d71408190aec0d5c2001b1cff completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f6827ecae8819092c15bbb1529dbad completed May 2, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_6a5a67a96f8c8190ab83bf9372e975e2 completed July 17, 2026, 5:34 p.m.
NEDg Description generation batch_6a5a684c57648190b7c505bfb60bfc25 completed July 17, 2026, 5:37 p.m.
NED2 Entity disambiguation (via description) batch_6a5a69da98408190867c1ab46b93e07f completed July 17, 2026, 5:43 p.m.
Created at: April 29, 2026, 7:58 p.m.