Triple

T12442588
Position Surface form Disambiguated ID Type / Status
Subject Buendia station E297312 entity
Predicate hasStationCode P1289 FINISHED
Object BU
BU is the station code for Buendia station, a rail transit stop in the Philippines.
 E984850 NE FINISHED

How this triple was built (4 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: BU | Statement: [Buendia station, hasStationCode, BU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: BU
Context triple: [Buendia station, hasStationCode, BU]
  • A. BU
    BU is a major private research university in Boston, Massachusetts, known for its diverse academic programs and global student body.
  • B. BU
    BU is a historic vehicle registration prefix that was once used to identify motor vehicles registered in Buckinghamshire, England.
  • C. BU
    BU is a private university in Peoria, Illinois, known for its comprehensive academic programs and strong emphasis on experiential learning.
  • D. BU
    BU is a modern public university located in Bournemouth, England, known for its strong industry links and career-focused courses, particularly in media, business, and tourism.
  • E. BU
    BU is the commonly used abbreviation for Bloomsburg University of Pennsylvania, a public university located in Bloomsburg, Pennsylvania.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: BU
Triple: [Buendia station, hasStationCode, BU]
Generated description
BU is the station code for Buendia station, a rail transit stop in the Philippines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: BU
Target entity description: BU is the station code for Buendia station, a rail transit stop in the Philippines.
  • A. BU
    BU is the commonly used abbreviation for Bloomsburg University of Pennsylvania, a public university located in Bloomsburg, Pennsylvania.
  • B. BU
    BU is a historic vehicle registration prefix that was once used to identify motor vehicles registered in Buckinghamshire, England.
  • C. BU
    BU is a public university located in Bhopal, Madhya Pradesh, India, offering a wide range of undergraduate, postgraduate, and research programs across various disciplines.
  • D. BU
    BU is a private university in Peoria, Illinois, known for its comprehensive academic programs and strong emphasis on experiential learning.
  • E. BU
    BU is a modern public university located in Bournemouth, England, known for its strong industry links and career-focused courses, particularly in media, business, and tourism.
  • F. None of above. chosen

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_69d6ada166c48190b902972cd2408fa3 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94d8ecb6c8190a19cbf9de31cabbd completed April 10, 2026, 7:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63f10926881909ffc641f8d19f93a completed May 2, 2026, 6:14 p.m.
NEDg Description generation batch_69f640874a0481908d9203b48304d866 completed May 2, 2026, 6:20 p.m.
NED2 Entity disambiguation (via description) batch_69f641287f888190bc7000c256c362d3 completed May 2, 2026, 6:23 p.m.
Created at: April 8, 2026, 9:55 p.m.