Triple

T3758671
Position Surface form Disambiguated ID Type / Status
Subject Tunis Metro E82109 entity
Predicate hasLine P35 FINISHED
Object Line 2
Line 2 is a major route of the Tunis Metro light rail network, serving key districts within the Tunis metropolitan area.
E386963 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 2 | Statement: [Tunis Metro, hasLine, Line 2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Line 2
Context triple: [Tunis Metro, hasLine, Line 2]
  • A. Line 2
    Line 2 is a major route of Mexico City’s Metrobús bus rapid transit system, running along key thoroughfares to connect important residential and commercial areas.
  • B. Line 2
    Line 2 is one of the main lines of the Santiago Metro in Chile, running in a generally north–south direction and serving several central and densely populated areas of the city.
  • C. Line 2
    Line 2 is a planned second rapid transit line of the Turin Metro system in Turin, Italy, intended to expand the city's urban rail network.
  • D. Line 2
    Line 2 is a Culver CityBus route in the Los Angeles area that provides local public transit service connecting key neighborhoods and transit hubs.
  • E. Line 2
    Line 2 is a major subway line on Toronto's Bloor–Danforth corridor, running primarily east–west across 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 2
Triple: [Tunis Metro, hasLine, Line 2]
Generated description
Line 2 is a major route of the Tunis Metro light rail network, serving key districts within the Tunis metropolitan area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Line 2
Target entity description: Line 2 is a major route of the Tunis Metro light rail network, serving key districts within the Tunis metropolitan area.
  • A. Line 2
    Line 2 is a rapid transit line of the Barcelona Metro system that serves several central and northern neighborhoods of the city.
  • B. Line 2
    Line 2 is a major rapid transit route of the Guangzhou Metro system that runs through key urban districts and serves as one of the network’s primary north–south corridors.
  • C. Line 2
    Line 2 is one of the main lines of the Santiago Metro in Chile, running in a generally north–south direction and serving several central and densely populated areas of the city.
  • D. Line 2
    Line 2 is one of the main rapid transit routes of the Athens Metro, connecting key central and suburban areas of the Greek capital.
  • E. Line 2
    Line 2 is a major east–west rapid transit route of the Shanghai Metro that connects key commercial, residential, and airport hubs across 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_69b4e5133ba48190a18ea170e3b9e1cd completed March 14, 2026, 4:33 a.m.
NEDg Description generation batch_69b4e62d284881908531b93645649f45 completed March 14, 2026, 4:38 a.m.
NED2 Entity disambiguation (via description) batch_69b4ea2b19e48190864d2114603865ed completed March 14, 2026, 4:55 a.m.
Created at: March 8, 2026, 3:35 p.m.