Triple

T12155928
Position Surface form Disambiguated ID Type / Status
Subject Cubao MRT station E289573 entity
Predicate hasStationCode P1289 FINISHED
Object CU
CU is the station code used to identify Cubao station on Manila’s MRT Line 3.
 E963468 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: CU | Statement: [Cubao MRT station, hasStationCode, CU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CU
Context triple: [Cubao MRT station, hasStationCode, CU]
  • A. CU
    CU is the two-letter ISO 3166-1 alpha-2 country code assigned to Cuba.
  • B. CU
    CU is the common abbreviation for Chulalongkorn University, a leading public research university in Bangkok, Thailand.
  • C. CU
    CU is the commonly used abbreviation for Ciudad Universitaria, a major university campus area in Spanish-speaking regions.
  • D. CU
    CU is the commonly used abbreviation for the multi-campus University of Colorado public university system in the United States.
  • E. CU
    CU is the common abbreviation for the Christian Union, a Christian student organization found at many universities.
  • 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: CU
Triple: [Cubao MRT station, hasStationCode, CU]
Generated description
CU is the station code used to identify Cubao station on Manila’s MRT Line 3.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CU
Target entity description: CU is the station code used to identify Cubao station on Manila’s MRT Line 3.
  • A. CU
    CU is the two-letter ISO 3166-1 alpha-2 country code assigned to Cuba.
  • B. CU
    CU is the common abbreviation for Chulalongkorn University, a leading public research university in Bangkok, Thailand.
  • C. CU
    CU is the common abbreviation for the Christian Union, a Christian student organization found at many universities.
  • D. CU
    CU is the commonly used abbreviation for Ciudad Universitaria, a major university campus area in Spanish-speaking regions.
  • E. CU
    CU is the commonly used abbreviation for the multi-campus University of Colorado public university system in the United States.
  • 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_69d6ab4c6710819097a9d228382dde43 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d915c1673c8190830cd15525d16869 completed April 10, 2026, 3:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f69c8d408190abbc900deb534045 completed May 2, 2026, 1:05 p.m.
NEDg Description generation batch_69f5fe53d47c8190896a9abf8cc4bc31 completed May 2, 2026, 1:38 p.m.
NED2 Entity disambiguation (via description) batch_69f5ffc2cfd08190b87eccd3a73afc77 completed May 2, 2026, 1:44 p.m.
Created at: April 8, 2026, 9:50 p.m.