Triple

T15827873
Position Surface form Disambiguated ID Type / Status
Subject Piața Victoriei metro station E383790 entity
Predicate hasStationCode P1289 FINISHED
Object PV
PV is the station code used to identify Piața Victoriei metro station in the Bucharest Metro system.
 E1178841 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: PV | Statement: [Piața Victoriei metro station, hasStationCode, PV]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: PV
Context triple: [Piața Victoriei metro station, hasStationCode, PV]
  • A. PV
    PV is the post-nominal abbreviation used to denote recipients of the Padma Vibhushan, one of India’s highest civilian honors.
  • B. PV
    PV is the vehicle registration code used on license plates for the Italian province of Pavia.
  • C. PJ
    PJ is the common abbreviation for Petaling Jaya, a major city in the state of Selangor, Malaysia, known for its residential suburbs and commercial centers.
  • D. PJ
    PJ is the commonly used abbreviation for Portugal’s Judiciary Police, the national criminal investigation police force.
  • E. PJ
    PJ is the station code for Port Jervis station, a commuter rail terminus serving the city of Port Jervis, New York.
  • 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: PV
Triple: [Piața Victoriei metro station, hasStationCode, PV]
Generated description
PV is the station code used to identify Piața Victoriei metro station in the Bucharest Metro system.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: PV
Target entity description: PV is the station code used to identify Piața Victoriei metro station in the Bucharest Metro system.
  • A. PV
    PV is the post-nominal abbreviation used to denote recipients of the Padma Vibhushan, one of India’s highest civilian honors.
  • B. PV
    PV is the vehicle registration code used on license plates for the Italian province of Pavia.
  • C. PJ
    PJ is the common abbreviation for Petaling Jaya, a major city in the state of Selangor, Malaysia, known for its residential suburbs and commercial centers.
  • D. PJ
    PJ is the commonly used abbreviation for Portugal’s Judiciary Police, the national criminal investigation police force.
  • E. PJ
    PJ is the station code for Port Jervis station, a commuter rail terminus serving the city of Port Jervis, New York.
  • 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_69d86da34c888190976e06c4019d415a completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e11e61c7508190ba1f675f2092364c completed April 16, 2026, 5:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff999da5008190921b3f129787999e completed May 9, 2026, 8:31 p.m.
NEDg Description generation batch_69ff9a82cadc8190a57f40062d29a998 completed May 9, 2026, 8:35 p.m.
NED2 Entity disambiguation (via description) batch_69ff9b5dbf80819085fdfcdff424511b completed May 9, 2026, 8:38 p.m.
Created at: April 10, 2026, 4:49 a.m.