Triple
T23493050
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Innsbruck tram system |
E571627
|
entity |
| Predicate | hasLine |
P35
|
FINISHED |
| Object |
Line 6
Line 6 is a scenic tram route in Innsbruck, Austria, known for its picturesque journey through mountainous and forested areas on the city’s tram network.
|
E1588510
|
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 6 | Statement: [Innsbruck tram system, hasLine, Line 6]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line 6 Context triple: [Innsbruck tram system, hasLine, Line 6]
-
A.
Line 6
Line 6 is a major rapid transit route in the Beijing Subway system that runs east–west across the city, helping to relieve congestion on other central lines.
-
B.
Line 6
Line 6 is a major north–south route of the Tehran Metro system, serving numerous key districts across Iran’s capital city.
-
C.
Line 6
Line 6 is a planned rapid transit route within the future Ho Chi Minh City Metro system in Vietnam.
-
D.
Line 6
Line 6 is a route of the Tunis Metro light rail network serving passengers within the Tunis metropolitan area.
-
E.
Line 6
Line 6 is one of the lines of the Paris Métro, known for its largely elevated route offering views of the city, including the Eiffel Tower.
- 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 6 Triple: [Innsbruck tram system, hasLine, Line 6]
Generated description
Line 6 is a scenic tram route in Innsbruck, Austria, known for its picturesque journey through mountainous and forested areas on the city’s tram network.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Line 6 Target entity description: Line 6 is a scenic tram route in Innsbruck, Austria, known for its picturesque journey through mountainous and forested areas on the city’s tram network.
-
A.
Line 6
Line 6 is a rapid transit route of the Brussels Metro system that serves key stations in Belgium’s capital.
-
B.
Line 6
Line 6 is a modern, fully automated metro line in the Santiago Metro system in Chile, known for its driverless trains and advanced safety features.
-
C.
Line 6
Line 6 is one of the lines of the Paris Métro, known for its largely elevated route offering views of the city, including the Eiffel Tower.
-
D.
Line 6
Line 6 is a rapid transit line of the Shanghai Metro system serving several districts along the city’s eastern side.
-
E.
Line 6
Line 6 is a major route of the Seoul Metropolitan Subway system that runs in a semi-circular path through northern Seoul, connecting numerous residential and commercial districts.
- 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_69e245b4829881909b77a70e942bbd54 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a7dd56408190b459077e433ed1c3 |
completed | April 29, 2026, 6:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c826ff3848190a3cdf82c26b6e22e |
completed | May 19, 2026, 3:32 p.m. |
| NEDg | Description generation | batch_6a0ca6f229308190bf72b52fd44144d3 |
completed | May 19, 2026, 6:07 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0ca7e9e9988190ac3bedb9ecb8ce06 |
completed | May 19, 2026, 6:11 p.m. |
Created at: April 17, 2026, 6:05 p.m.