Triple

T10351728
Position Surface form Disambiguated ID Type / Status
Subject Nyugati tér E243896 entity
Predicate hasTramLine P17788 FINISHED
Object Tram line 4
Tram line 4 is one of Budapest’s busiest urban tram routes, running across the city center and connecting major hubs including Nyugati tér.
 E857886 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 line 4 | Statement: [Nyugati tér, hasTramLine, Tram line 4]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tram line 4
Context triple: [Nyugati tér, hasTramLine, Tram line 4]
  • A. Tram 14
    Tram 14 is a major tram line in Geneva’s public transport system, connecting key districts and suburbs within the city.
  • B. Tram 15
    Tram 15 is a major tram line in Geneva’s public transport system, connecting key districts across the city and its suburbs.
  • C. Tram 17
    Tram 17 is a tram line in Geneva’s public transport system operated by the city’s transit authority.
  • D. Tram 12
    Tram 12 is a major tram line in Geneva’s public transport system, connecting key neighborhoods and suburbs across the city.
  • E. Tram 18
    Tram 18 is a tram line in Geneva’s public transport system that connects key districts within the city and its surrounding areas.
  • 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 line 4
Triple: [Nyugati tér, hasTramLine, Tram line 4]
Generated description
Tram line 4 is one of Budapest’s busiest urban tram routes, running across the city center and connecting major hubs including Nyugati tér.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tram line 4
Target entity description: Tram line 4 is one of Budapest’s busiest urban tram routes, running across the city center and connecting major hubs including Nyugati tér.
  • A. Tram 14
    Tram 14 is a major tram line in Geneva’s public transport system, connecting key districts and suburbs within the city.
  • B. Tram 15
    Tram 15 is a major tram line in Geneva’s public transport system, connecting key districts across the city and its suburbs.
  • C. Tram 17
    Tram 17 is a tram line in Geneva’s public transport system operated by the city’s transit authority.
  • D. Tram 12
    Tram 12 is a major tram line in Geneva’s public transport system, connecting key neighborhoods and suburbs across the city.
  • E. Tram 18
    Tram 18 is a tram line in Geneva’s public transport system that connects key districts within the city and its surrounding areas.
  • 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_69d381b22b8c8190aaed476be5f872a9 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9489f9481908fc1c818e81c1cc2 completed April 7, 2026, 11:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69d75095625c819082d4d0976a193e6c completed April 9, 2026, 7:09 a.m.
NEDg Description generation batch_69d7618da0188190901026dd51ceaa46 completed April 9, 2026, 8:21 a.m.
NED2 Entity disambiguation (via description) batch_69d77045ea988190bd8e31f5f636f69b completed April 9, 2026, 9:24 a.m.
Created at: April 6, 2026, 11:57 a.m.