Triple

T8857661
Position Surface form Disambiguated ID Type / Status
Subject Landeck E210798 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object LA
LA is the vehicle registration code used for the district of Landeck in the Austrian state of Tyrol.
 E768924 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: LA | Statement: [Landeck, vehicleRegistrationCode, LA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LA
Context triple: [Landeck, vehicleRegistrationCode, LA]
  • A. LA
    LA is the IATA airline designator used by LATAM Airlines Group, a major South American airline conglomerate.
  • B. LA
    LA is the postcode area covering Lancaster and surrounding parts of north-west England, including parts of Cumbria and Lancashire.
  • C. LA
    LA is the official two-letter U.S. Postal Service abbreviation for the state of Louisiana.
  • D. LA
    LA is the standard abbreviation for the Lord Advocate, the chief legal officer of the Scottish Government and the Crown in Scotland.
  • E. Los Angeles
    Los Angeles is a major U.S. metropolis known for its entertainment industry, cultural diversity, and sprawling urban landscape.
  • 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: LA
Triple: [Landeck, vehicleRegistrationCode, LA]
Generated description
LA is the vehicle registration code used for the district of Landeck in the Austrian state of Tyrol.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LA
Target entity description: LA is the vehicle registration code used for the district of Landeck in the Austrian state of Tyrol.
  • A. LA
    LA is the IATA airline designator used by LATAM Airlines Group, a major South American airline conglomerate.
  • B. LA
    LA is the postcode area covering Lancaster and surrounding parts of north-west England, including parts of Cumbria and Lancashire.
  • C. LA
    LA is the official two-letter U.S. Postal Service abbreviation for the state of Louisiana.
  • D. LA
    LA is the standard abbreviation for the Lord Advocate, the chief legal officer of the Scottish Government and the Crown in Scotland.
  • E. Los Angeles
    Los Angeles is a major U.S. metropolis known for its entertainment industry, cultural diversity, and sprawling urban landscape.
  • 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_69ca838bbddc8190ab546d737e5d350f completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc60e3b62c8190bf779e7e1db767f6 completed April 1, 2026, 12:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc929fb94819091980b0994b4f02d completed April 3, 2026, 2:05 p.m.
NEDg Description generation batch_69cfca00ffa08190ad66fb99572a6275 completed April 3, 2026, 2:09 p.m.
NED2 Entity disambiguation (via description) batch_69cfca84937881909707497d733218e5 completed April 3, 2026, 2:11 p.m.
Created at: March 30, 2026, 6:50 p.m.