Triple

T3701815
Position Surface form Disambiguated ID Type / Status
Subject Troms E80793 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object T
T is the vehicle registration code used for motor vehicles registered in Troms county in Norway.
 E381861 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: T | Statement: [Troms, vehicleRegistrationCode, T]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: T
Context triple: [Troms, vehicleRegistrationCode, T]
  • A. the T
    The T is the public transit system serving the Greater Boston area, operated by the Massachusetts Bay Transportation Authority.
  • B. TA
    TA is a common abbreviation for the Territorial Army, a volunteer reserve force that supports a country's regular armed forces.
  • C. TA
    TA is the standard abbreviation for *Transforming Anthropology*, a peer-reviewed academic journal focusing on critical and innovative scholarship in anthropology.
  • D. TA
    TA is the IATA airline designator assigned to TACA Airlines, a major Central American carrier that later merged into Avianca.
  • E. tet
    tet is the ISO 639-1 language code for Tetum, an Austronesian language spoken primarily in East Timor.
  • 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: T
Triple: [Troms, vehicleRegistrationCode, T]
Generated description
T is the vehicle registration code used for motor vehicles registered in Troms county in Norway.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: T
Target entity description: T is the vehicle registration code used for motor vehicles registered in Troms county in Norway.
  • A. the T
    The T is the public transit system serving the Greater Boston area, operated by the Massachusetts Bay Transportation Authority.
  • B. TA
    TA is a common abbreviation for the Territorial Army, a volunteer reserve force that supports a country's regular armed forces.
  • C. TA
    TA is the standard abbreviation for *Transforming Anthropology*, a peer-reviewed academic journal focusing on critical and innovative scholarship in anthropology.
  • D. TA
    TA is the IATA airline designator assigned to TACA Airlines, a major Central American carrier that later merged into Avianca.
  • E. tet
    tet is the ISO 639-1 language code for Tetum, an Austronesian language spoken primarily in East Timor.
  • 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_69ad8b1793888190a5f70e4b21dc05a1 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adc547c1848190a1ece46c59b7c43d completed March 8, 2026, 6:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4cdf53190819098529d11a5a3c7a8 completed March 14, 2026, 2:54 a.m.
NEDg Description generation batch_69b4cf799ae88190bbf821f4c4500031 completed March 14, 2026, 3:01 a.m.
NED2 Entity disambiguation (via description) batch_69b4d0057fe8819092a40732324f88c9 completed March 14, 2026, 3:03 a.m.
Created at: March 8, 2026, 3:33 p.m.