Triple

T2212072
Position Surface form Disambiguated ID Type / Status
Subject Geneva public transport network E50939 entity
Predicate hasTramLine P17788 FINISHED
Object Tram 17
Tram 17 is a tram line in Geneva’s public transport system operated by the city’s transit authority.
 E252055 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: Tram 17 | Statement: [Geneva public transport network, hasTramLine, Tram 17]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tram 17
Context triple: [Geneva public transport network, hasTramLine, Tram 17]
  • A. Tram 15
    Tram 15 is a major tram line in Geneva’s public transport system, connecting key districts across the city and its suburbs.
  • B. Tram 14
    Tram 14 is a major tram line in Geneva’s public transport system, connecting key districts and suburbs within the city.
  • C. Tram 12
    Tram 12 is a major tram line in Geneva’s public transport system, connecting key neighborhoods and suburbs across the city.
  • D. Trolebús
    Trolebús is an electric trolleybus transit system serving Mexico City as part of its broader public transportation network.
  • E. SL95 tram
    The SL95 tram is a high-floor, bi-directional tram model used in Oslo, Norway, known for its large capacity and operation on the city’s light rail and tram network.
  • 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: Tram 17
Triple: [Geneva public transport network, hasTramLine, Tram 17]
Generated description
Tram 17 is a tram line in Geneva’s public transport system operated by the city’s transit authority.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tram 17
Target entity description: Tram 17 is a tram line in Geneva’s public transport system operated by the city’s transit authority.
  • A. Tram 15
    Tram 15 is a major tram line in Geneva’s public transport system, connecting key districts across the city and its suburbs.
  • B. Tram 14
    Tram 14 is a major tram line in Geneva’s public transport system, connecting key districts and suburbs within the city.
  • C. Tram 12
    Tram 12 is a major tram line in Geneva’s public transport system, connecting key neighborhoods and suburbs across the city.
  • D. Trolebús
    Trolebús is an electric trolleybus transit system serving Mexico City as part of its broader public transportation network.
  • E. SL95 tram
    The SL95 tram is a high-floor, bi-directional tram model used in Oslo, Norway, known for its large capacity and operation on the city’s light rail and tram network.
  • 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_69a88b06709c8190978fb2418470d1b6 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc5b101d48190a321625720d537b6 completed March 7, 2026, 6:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae7efdb7a08190b74e841279b59971 completed March 9, 2026, 8:04 a.m.
NEDg Description generation batch_69ae7f90d3a88190bf61c6f063b67c06 completed March 9, 2026, 8:06 a.m.
NED2 Entity disambiguation (via description) batch_69ae800868948190a5504969c4cabb7d completed March 9, 2026, 8:08 a.m.
Created at: March 4, 2026, 7:46 p.m.