Triple

T3758674
Position Surface form Disambiguated ID Type / Status
Subject Tunis Metro E82109 entity
Predicate hasLine P35 FINISHED
Object Line 5
Line 5 is one of the routes of the Tunis Metro light rail network, serving passengers across part of the Tunis metropolitan area.
E394132 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: Line 5 | Statement: [Tunis Metro, hasLine, Line 5]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Line 5
Context triple: [Tunis Metro, hasLine, Line 5]
  • A. Line 5
    Line 5 is one of the main lines of the Santiago Metro in Chile, running across several key districts and serving as a major east–west transit corridor in the city.
  • B. Line 5
    Line 5 is a major north–south route of the Beijing Subway known for connecting key residential and commercial areas through the city center.
  • C. Line 5
    Line 5 is a major east–west rapid transit route in the Guangzhou Metro system, serving key urban districts and facilitating high-capacity cross-city travel.
  • D. Line 5
    Line 5 is a commuter rail line of the Tehran Metro system that connects central Tehran with its western suburbs and satellite cities.
  • E. Line 5
    Line 5 is a rapid transit line of the Shanghai Metro system serving the southern suburbs of the city.
  • 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: Line 5
Triple: [Tunis Metro, hasLine, Line 5]
Generated description
Line 5 is one of the routes of the Tunis Metro light rail network, serving passengers across part of the Tunis metropolitan area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Line 5
Target entity description: Line 5 is one of the routes of the Tunis Metro light rail network, serving passengers across part of the Tunis metropolitan area.
  • A. Line 5
    Line 5 is a major line of the Barcelona Metro rapid transit system, serving numerous key neighborhoods and transport hubs across the city.
  • B. Line 5
    Line 5 is a major east–west route of the Brussels Metro system, connecting key districts across the Belgian capital.
  • C. Line 5
    Line 5 is a planned rapid transit route of the Ho Chi Minh City Metro system intended to serve as part of the city’s future urban rail network.
  • D. Line 5
    Line 5 is a rapid transit line of the Shanghai Metro system serving the southern suburbs of the city.
  • E. Line 5
    Line 5 is one of the main lines of the Santiago Metro in Chile, running across several key districts and serving as a major east–west transit corridor in the city.
  • 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_69ad8b1db40081908b61ffa6b78afd4d completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcbc20b20819095fedf803aadc53a completed March 8, 2026, 7:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69b503e6c48881909ac813e603175eb0 completed March 14, 2026, 6:44 a.m.
NEDg Description generation batch_69b50f2492c4819095dd2ccccc62b287 completed March 14, 2026, 7:32 a.m.
NED2 Entity disambiguation (via description) batch_69b50f8249488190a9d399c43238047f completed March 14, 2026, 7:34 a.m.
Created at: March 8, 2026, 3:35 p.m.