Triple

T13427025
Position Surface form Disambiguated ID Type / Status
Subject Education City E313507 entity
Predicate hasMetroStation P522 FINISHED
Object Education City station E313507 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: Education City station | Statement: [Education City, hasMetroStation, Education City station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Education City station
Context triple: [Education City, hasMetroStation, Education City station]
  • A. University City station
    University City station is a SEPTA regional rail stop in Philadelphia serving the University City district and nearby academic and medical institutions.
  • B. Education City
    Education City is a nickname for Rajshahi, a major city in Bangladesh renowned for its high concentration of universities and educational institutions.
  • C. Education City chosen
    Education City is a large academic hub on the outskirts of Doha, Qatar, that hosts branch campuses of several leading international universities and research institutions.
  • D. University Station
    University Station is a major mixed-use retail and commercial shopping complex serving the Westwood, Massachusetts area.
  • E. University Station
    University Station is a light rail transit stop on Edmonton's LRT network serving the University of Alberta area.
  • 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_69d806ad0c44819088833ae1ec9e9690 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaed1f9208190bf5ef5b8a7ded376 completed April 12, 2026, 2:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f730883cb48190add9469c48dc3e89 completed May 3, 2026, 11:24 a.m.
Created at: April 9, 2026, 9:40 p.m.