Triple

T17210258
Position Surface form Disambiguated ID Type / Status
Subject Zduńska Wola railway station E417708 entity
Predicate railwayStationCode P1289 FINISHED
Object PZDW
PZDW is the station code for Zduńska Wola railway station in central Poland, a stop on important regional and intercity rail routes.
 E1255346 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: PZDW | Statement: [Zduńska Wola railway station, railwayStationCode, PZDW]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: PZDW
Context triple: [Zduńska Wola railway station, railwayStationCode, PZDW]
  • A. PZ
    PZ is the vehicle registration code used on license plates for vehicles registered in the Preveza regional unit of Greece.
  • B. PZ
    PZ is the IATA airline designator assigned to LATAM Airlines Paraguay, the Paraguayan branch of the LATAM Airlines Group.
  • C. PZ
    PZ is the Italian vehicle registration code assigned to the Province of Potenza in the Basilicata region.
  • D. PZ
    PZ is the commonly used abbreviation for Peshawar Zalmi, a professional cricket franchise that competes in the Pakistan Super League.
  • E. PZ
    PZ is the station code for Prinzregentenplatz, a Munich U-Bahn station on the city’s rapid transit network.
  • 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: PZDW
Triple: [Zduńska Wola railway station, railwayStationCode, PZDW]
Generated description
PZDW is the station code for Zduńska Wola railway station in central Poland, a stop on important regional and intercity rail routes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: PZDW
Target entity description: PZDW is the station code for Zduńska Wola railway station in central Poland, a stop on important regional and intercity rail routes.
  • A. PZ
    PZ is the vehicle registration code used on license plates for vehicles registered in the Preveza regional unit of Greece.
  • B. PZ
    PZ is the IATA airline designator assigned to LATAM Airlines Paraguay, the Paraguayan branch of the LATAM Airlines Group.
  • C. PZ
    PZ is the station code for Prinzregentenplatz, a Munich U-Bahn station on the city’s rapid transit network.
  • D. PZ
    PZ is the commonly used abbreviation for Peshawar Zalmi, a professional cricket franchise that competes in the Pakistan Super League.
  • E. PZ
    PZ is the Italian vehicle registration code assigned to the Province of Potenza in the Basilicata region.
  • 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_69d886d779488190b131369541c04e7d completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42dc4792081909443df7937768ede completed April 19, 2026, 1:20 a.m.
NED1 Entity disambiguation (via context triple) batch_6a015fe217308190b6ae1e98d0c421e4 completed May 11, 2026, 4:49 a.m.
NEDg Description generation batch_6a0160e95f1481908058aed285968991 completed May 11, 2026, 4:54 a.m.
NED2 Entity disambiguation (via description) batch_6a01617888ac8190af2a91a4bd28b402 completed May 11, 2026, 4:56 a.m.
Created at: April 10, 2026, 5:38 a.m.