Triple

T10128581
Position Surface form Disambiguated ID Type / Status
Subject Gniezno E226276 entity
Predicate hasVehicleRegistrationCode P1173 FINISHED
Object PGN
PGN is the vehicle registration code assigned to the city of Gniezno in Poland.
 E841725 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: PGN | Statement: [Gniezno, hasVehicleRegistrationCode, PGN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: PGN
Context triple: [Gniezno, hasVehicleRegistrationCode, PGN]
  • A. PGPL
    PGPL is the top professional football league in Iran, featuring the country’s leading clubs in the highest tier of its league system.
  • B. KGS
    KGS is the IATA airport code for Kos Island International Airport, which serves the Greek island of Kos in the Aegean Sea.
  • C. KGS
    KGS is the official currency code for the Kyrgyzstani som, the national currency of Kyrgyzstan.
  • D. PGSN
    PGSN is the ICAO airport code for Saipan International Airport, the main airport serving Saipan in the Northern Mariana Islands.
  • E. PGF
    PGF is the IATA airport code for Perpignan–Rivesaltes Airport in southern France.
  • 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: PGN
Triple: [Gniezno, hasVehicleRegistrationCode, PGN]
Generated description
PGN is the vehicle registration code assigned to the city of Gniezno in Poland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: PGN
Target entity description: PGN is the vehicle registration code assigned to the city of Gniezno in Poland.
  • A. PGPL
    PGPL is the top professional football league in Iran, featuring the country’s leading clubs in the highest tier of its league system.
  • B. KGS
    KGS is the IATA airport code for Kos Island International Airport, which serves the Greek island of Kos in the Aegean Sea.
  • C. KGS
    KGS is the official currency code for the Kyrgyzstani som, the national currency of Kyrgyzstan.
  • D. PGSN
    PGSN is the ICAO airport code for Saipan International Airport, the main airport serving Saipan in the Northern Mariana Islands.
  • E. PGF
    PGF is the IATA airport code for Perpignan–Rivesaltes Airport in southern France.
  • 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_69ca843057b48190a86730167f5d6b98 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cdd2f0a0e881909267a83fbeb31f0c completed April 2, 2026, 2:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2cc72848481909dcbfc9fe3f6d379 completed April 5, 2026, 8:56 p.m.
NEDg Description generation batch_69d2cda6452c81908d67ea322da3cf70 completed April 5, 2026, 9:01 p.m.
NED2 Entity disambiguation (via description) batch_69d2ce71fa888190b8dd13df83a2cd78 completed April 5, 2026, 9:04 p.m.
Created at: March 30, 2026, 9:05 p.m.