Triple

T8057596
Position Surface form Disambiguated ID Type / Status
Subject Messkirch E188039 entity
Predicate hasVehicleRegistrationCode P1173 FINISHED
Object SIG
SIG is the vehicle registration code for the district of Sigmaringen in the German state of Baden-Württemberg.
 E707126 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: SIG | Statement: [Messkirch, hasVehicleRegistrationCode, SIG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SIG
Context triple: [Messkirch, hasVehicleRegistrationCode, SIG]
  • A. SIG
    SIG is an acronym commonly used by the Association for Computing Machinery to denote its specialized Special Interest Groups that focus on particular areas of computing research and practice.
  • B. SIG
    SIG is the public utility company of Geneva, Switzerland, responsible for providing services such as electricity, gas, water, and energy solutions to the region.
  • C. SIG
    SIG is the IATA airport code for Fernando Luis Ribas Dominicci Airport, a regional airport serving San Juan, Puerto Rico.
  • D. Sigma
    Sigma is a Greek letter commonly used in mathematics, science, and engineering to denote summation, standard deviation, and various other concepts.
  • E. Sigma
    Sigma is a rural municipality in the province of Capiz in the Western Visayas region of the Philippines, known for its agricultural economy and small-town character.
  • 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: SIG
Triple: [Messkirch, hasVehicleRegistrationCode, SIG]
Generated description
SIG is the vehicle registration code for the district of Sigmaringen in the German state of Baden-Württemberg.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SIG
Target entity description: SIG is the vehicle registration code for the district of Sigmaringen in the German state of Baden-Württemberg.
  • A. SIG
    SIG is an acronym commonly used by the Association for Computing Machinery to denote its specialized Special Interest Groups that focus on particular areas of computing research and practice.
  • B. SIG
    SIG is the public utility company of Geneva, Switzerland, responsible for providing services such as electricity, gas, water, and energy solutions to the region.
  • C. SIG
    SIG is the IATA airport code for Fernando Luis Ribas Dominicci Airport, a regional airport serving San Juan, Puerto Rico.
  • D. Sigma
    Sigma is a Greek letter commonly used in mathematics, science, and engineering to denote summation, standard deviation, and various other concepts.
  • E. Sigma
    Sigma is a rural municipality in the province of Capiz in the Western Visayas region of the Philippines, known for its agricultural economy and small-town character.
  • 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_69ca82b2f68881908c50560697e210da completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3fa3dd2481909e925304fcea2111 completed March 31, 2026, 3:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc572a87788190a92f96f7b9c43f2a completed March 31, 2026, 11:22 p.m.
NEDg Description generation batch_69cc58ee56108190b93f0bf6bbb0321c completed March 31, 2026, 11:29 p.m.
NED2 Entity disambiguation (via description) batch_69cc5cd22b188190b8a31e8e8ac8b98d completed March 31, 2026, 11:46 p.m.
Created at: March 30, 2026, 5:25 p.m.