Triple

T2542175
Position Surface form Disambiguated ID Type / Status
Subject LRT Line 2 E57808 entity
Predicate hasStation P35 FINISHED
Object V. Mapa station
V. Mapa station is an elevated Manila Light Rail Transit Line 2 station located in the Santa Mesa area of Manila, Philippines.
 E277586 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: V. Mapa station | Statement: [LRT Line 2, hasStation, V. Mapa station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: V. Mapa station
Context triple: [LRT Line 2, hasStation, V. Mapa station]
  • A. Khimvolokno station
    Khimvolokno station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
  • B. Kachinskaya station
    Kachinskaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
  • C. Kommunarka station
    Kommunarka station is a southern terminal metro station on Moscow’s Sokolnicheskaya Line, serving the rapidly developing Kommunarka district.
  • D. Innovation Center station
    Innovation Center station is a Washington Metro rail station in Virginia located near the Dulles Technology Corridor, serving the Silver Line.
  • E. Yelshanka station
    Yelshanka station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
  • 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: V. Mapa station
Triple: [LRT Line 2, hasStation, V. Mapa station]
Generated description
V. Mapa station is an elevated Manila Light Rail Transit Line 2 station located in the Santa Mesa area of Manila, Philippines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: V. Mapa station
Target entity description: V. Mapa station is an elevated Manila Light Rail Transit Line 2 station located in the Santa Mesa area of Manila, Philippines.
  • A. Khimvolokno station
    Khimvolokno station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
  • B. Kachinskaya station
    Kachinskaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
  • C. Kommunarka station
    Kommunarka station is a southern terminal metro station on Moscow’s Sokolnicheskaya Line, serving the rapidly developing Kommunarka district.
  • D. Innovation Center station
    Innovation Center station is a Washington Metro rail station in Virginia located near the Dulles Technology Corridor, serving the Silver Line.
  • E. Yelshanka station
    Yelshanka station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
  • 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_69ab4a5212d88190b989ce129f2ad87f completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd2bd92f88190bf100c799f62210c completed March 7, 2026, 7:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69af5d046430819095605b8a8fd987d5 completed March 9, 2026, 11:51 p.m.
NEDg Description generation batch_69af5f4be20c8190a0da1a25c7b097b8 completed March 10, 2026, 12:01 a.m.
NED2 Entity disambiguation (via description) batch_69af5fe06e6881908e0b11f3101cb0f0 completed March 10, 2026, 12:03 a.m.
Created at: March 6, 2026, 9:47 p.m.