Triple

T5970620
Position Surface form Disambiguated ID Type / Status
Subject Basel tram network E132861 entity
Predicate fareSystem P395 FINISHED
Object TNW
TNW is the integrated public transport fare network covering Basel and its surrounding region in Switzerland.
 E559882 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: TNW | Statement: [Basel tram network, fareSystem, TNW]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TNW
Context triple: [Basel tram network, fareSystem, TNW]
  • A. TNN
    TNN, originally known as The Nashville Network, was a U.S. cable television channel that evolved from country-music-focused programming into a broader general entertainment network before rebranding as Spike.
  • B. TTO
    TTO is the FIFA country code representing the Trinidad and Tobago national football team in international competitions.
  • C. TTO
    TTO is a DARPA office focused on developing and demonstrating high-risk, high-payoff advanced military technologies and systems.
  • D. TN
    TN is the official two-letter U.S. Postal Service abbreviation for the state of Tennessee.
  • E. TN
    TN is the official vehicle registration code used for the Indian state of Tamil Nadu.
  • 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: TNW
Triple: [Basel tram network, fareSystem, TNW]
Generated description
TNW is the integrated public transport fare network covering Basel and its surrounding region in Switzerland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TNW
Target entity description: TNW is the integrated public transport fare network covering Basel and its surrounding region in Switzerland.
  • A. TNN
    TNN, originally known as The Nashville Network, was a U.S. cable television channel that evolved from country-music-focused programming into a broader general entertainment network before rebranding as Spike.
  • B. TTO
    TTO is the FIFA country code representing the Trinidad and Tobago national football team in international competitions.
  • C. TTO
    TTO is a DARPA office focused on developing and demonstrating high-risk, high-payoff advanced military technologies and systems.
  • D. TN
    TN is the official two-letter U.S. Postal Service abbreviation for the state of Tennessee.
  • E. TN
    TN is the official vehicle registration code used for the Indian state of Tamil Nadu.
  • 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_69c0086deab081908550159ca23eec9b completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c03a4263e8819084e98e6c016c9532 completed March 22, 2026, 6:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0e40a67bc8190a57884f7c6aa1b9d completed March 23, 2026, 6:56 a.m.
NEDg Description generation batch_69c0f88f4e048190810351c4aebf363c completed March 23, 2026, 8:23 a.m.
NED2 Entity disambiguation (via description) batch_69c0f982c95c819081b2cf2c429c21bc completed March 23, 2026, 8:27 a.m.
Created at: March 22, 2026, 4:03 p.m.