Triple

T7929204
Position Surface form Disambiguated ID Type / Status
Subject NHSL E184143 entity
Predicate formerName P65 FINISHED
Object Route 100 E184141 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: Route 100 | Statement: [NHSL, formerName, Route 100]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Route 100
Context triple: [NHSL, formerName, Route 100]
  • A. Route 100 chosen
    Route 100 is the former designation of the Norristown High Speed Line, an interurban rapid transit route in the Philadelphia metropolitan area.
  • B. Route 10
    Route 10 is a SEPTA subway–surface trolley line in Philadelphia that provides light rail service between Center City and the city’s western neighborhoods.
  • C. Route 110
    Route 110 is a poem by Seamus Heaney that reimagines episodes from Homer’s Odyssey within the landscapes and experiences of modern Ireland.
  • D. Route 107
    Route 107 is a state highway in Massachusetts that runs through cities such as Revere and Lynn, serving as a key north–south arterial route north of Boston.
  • E. Route 107
    Route 107 is a state highway in southwestern Connecticut that serves as a local connector through towns such as Redding and Georgetown.
  • 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_69ca828fe7bc819090f52c88dcd72183 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3acb6cb88190b4f31b7091881241 completed March 31, 2026, 3:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5c01602081908ea1af24785260ff completed March 31, 2026, 5:30 a.m.
Created at: March 30, 2026, 5:07 p.m.