Triple

T2753908
Position Surface form Disambiguated ID Type / Status
Subject Zamość E61054 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object LZA
LZA is the regional vehicle registration code assigned to motor vehicles registered in the city of Zamość in Poland.
 E295437 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: LZA | Statement: [Zamość, vehicleRegistrationCode, LZA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LZA
Context triple: [Zamość, vehicleRegistrationCode, LZA]
  • A. ZLP
    ZLP is the IATA station code for Zürich Hauptbahnhof, the main railway station in Zurich, Switzerland.
  • B. ZF
    ZF is the standard axiomatic framework for set theory that underpins much of modern mathematics.
  • C. Laz
    Laz is a South Caucasian (Kartvelian) language traditionally spoken by the Laz people along the southeastern Black Sea coast, particularly in northeastern Turkey and parts of Georgia.
  • D. Zip2
    Zip2 was an early online city guide and business directory software company from the late 1990s that provided web-based publishing tools for newspapers.
  • E. ZUE
    ZUE is the railway station code for Zürich Hauptbahnhof, Switzerland’s largest and busiest train station and a major European rail hub.
  • 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: LZA
Triple: [Zamość, vehicleRegistrationCode, LZA]
Generated description
LZA is the regional vehicle registration code assigned to motor vehicles registered in the city of Zamość in Poland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LZA
Target entity description: LZA is the regional vehicle registration code assigned to motor vehicles registered in the city of Zamość in Poland.
  • A. ZLP
    ZLP is the IATA station code for Zürich Hauptbahnhof, the main railway station in Zurich, Switzerland.
  • B. ZF
    ZF is the standard axiomatic framework for set theory that underpins much of modern mathematics.
  • C. Laz
    Laz is a South Caucasian (Kartvelian) language traditionally spoken by the Laz people along the southeastern Black Sea coast, particularly in northeastern Turkey and parts of Georgia.
  • D. Zip2
    Zip2 was an early online city guide and business directory software company from the late 1990s that provided web-based publishing tools for newspapers.
  • E. ZUE
    ZUE is the railway station code for Zürich Hauptbahnhof, Switzerland’s largest and busiest train station and a major European rail hub.
  • 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_69ab4b7a85bc819094a349b84beb1f2c completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdb7073d081909da84b21015972f2 completed March 7, 2026, 8:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69afbbdb43d481909bf4e61840979c0a completed March 10, 2026, 6:36 a.m.
NEDg Description generation batch_69afbc758cc48190a96f80a850316ce3 completed March 10, 2026, 6:38 a.m.
NED2 Entity disambiguation (via description) batch_69afbd7be9088190a19bed27249e95c4 completed March 10, 2026, 6:43 a.m.
Created at: March 6, 2026, 9:56 p.m.