Triple

T11969787
Position Surface form Disambiguated ID Type / Status
Subject Lębork E284885 entity
Predicate hasVehicleRegistrationCode P1173 FINISHED
Object GLE
GLE is the vehicle registration code assigned to the town of Lębork in northern Poland.
 E956393 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: GLE | Statement: [Lębork, hasVehicleRegistrationCode, GLE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: GLE
Context triple: [Lębork, hasVehicleRegistrationCode, GLE]
  • A. GLE
    The Mercedes-Benz GLE is a mid-size luxury SUV known for its premium comfort, advanced technology, and strong performance within the brand’s lineup.
  • B. GLE
    GLE is the stock ticker symbol for Société Générale, a major French multinational banking and financial services company.
  • C. GLE
    GLE is the FAA airport code for Gainesville Municipal Airport in Gainesville, Texas.
  • D. GL
    GL is the postcode area in the United Kingdom that covers Cheltenham and surrounding parts of Gloucestershire.
  • E. GL
    GL is the stock ticker symbol for Globe Life Inc., a U.S.-based life and health insurance company traded on the New York Stock Exchange.
  • 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: GLE
Triple: [Lębork, hasVehicleRegistrationCode, GLE]
Generated description
GLE is the vehicle registration code assigned to the town of Lębork in northern Poland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: GLE
Target entity description: GLE is the vehicle registration code assigned to the town of Lębork in northern Poland.
  • A. GLE
    The Mercedes-Benz GLE is a mid-size luxury SUV known for its premium comfort, advanced technology, and strong performance within the brand’s lineup.
  • B. GLE
    GLE is the stock ticker symbol for Société Générale, a major French multinational banking and financial services company.
  • C. GLE
    GLE is the FAA airport code for Gainesville Municipal Airport in Gainesville, Texas.
  • D. GL
    GL is the postcode area in the United Kingdom that covers Cheltenham and surrounding parts of Gloucestershire.
  • E. GL
    GL is the stock ticker symbol for Globe Life Inc., a U.S.-based life and health insurance company traded on the New York Stock Exchange.
  • 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_69d6ab2eaeb881909f7914758f859413 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9037bee54819085242a3ef3e286f9 completed April 10, 2026, 2:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69f459691ff0819099282172933d2d81 completed May 1, 2026, 7:42 a.m.
NEDg Description generation batch_69f4645ef63881909b46937f73d637a3 completed May 1, 2026, 8:29 a.m.
NED2 Entity disambiguation (via description) batch_69f465be4db08190882898a17d077019 completed May 1, 2026, 8:35 a.m.
Created at: April 8, 2026, 9:46 p.m.