Triple

T11738671
Position Surface form Disambiguated ID Type / Status
Subject J. Ruiz station E279095 entity
Predicate hasStationCode P1289 FINISHED
Object JR
JR is the station code assigned to J. Ruiz station in the Manila Metro Rail Transit system.
 E944266 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: JR | Statement: [J. Ruiz station, hasStationCode, JR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: JR
Context triple: [J. Ruiz station, hasStationCode, JR]
  • A. JR
    JR is a French street artist and photographer renowned for his large-scale public art installations that transform urban spaces and address social and political issues worldwide.
  • B. JR
    JR is a character from Alison Bechdel’s long-running comic strip "Dykes to Watch Out For," which chronicles the lives and relationships of a diverse group of lesbian friends.
  • C. RJ
    RJ is the two-letter IATA airline designator assigned to Royal Jordanian, the flag carrier airline of Jordan.
  • D. RJ
    RJ is the crafty, fast-talking raccoon who leads the animal ensemble in the animated film "Over the Hedge."
  • E. JT
    JT is a lightweight 3D visualization and data exchange file format commonly used in CAD and PLM workflows for efficient sharing of complex product models.
  • 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: JR
Triple: [J. Ruiz station, hasStationCode, JR]
Generated description
JR is the station code assigned to J. Ruiz station in the Manila Metro Rail Transit system.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: JR
Target entity description: JR is the station code assigned to J. Ruiz station in the Manila Metro Rail Transit system.
  • A. JR
    JR is a French street artist and photographer renowned for his large-scale public art installations that transform urban spaces and address social and political issues worldwide.
  • B. JR
    JR is a character from Alison Bechdel’s long-running comic strip "Dykes to Watch Out For," which chronicles the lives and relationships of a diverse group of lesbian friends.
  • C. RJ
    RJ is the two-letter IATA airline designator assigned to Royal Jordanian, the flag carrier airline of Jordan.
  • D. RJ
    RJ is the crafty, fast-talking raccoon who leads the animal ensemble in the animated film "Over the Hedge."
  • E. JT
    JT is a lightweight 3D visualization and data exchange file format commonly used in CAD and PLM workflows for efficient sharing of complex product models.
  • 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_69d6aaffec6881908bead509e8621742 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a4ef1c4881909ad36dc27b1fe193 completed April 10, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69f019c339cc81909967ecfa234e4ab8 completed April 28, 2026, 2:21 a.m.
NEDg Description generation batch_69f01d7ab930819095eaae226ab55b80 completed April 28, 2026, 2:37 a.m.
NED2 Entity disambiguation (via description) batch_69f043ddbfe481908e0c439dbd3e944f completed April 28, 2026, 5:21 a.m.
Created at: April 8, 2026, 9:41 p.m.