Triple
T7175659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Istanbul Metro |
E167312
|
entity |
| Predicate | hasLine |
P35
|
FINISHED |
| Object |
M15 line
The M15 line is a rapid transit route within the Istanbul Metro system that serves as part of the city's urban rail network.
|
E664630
|
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: M15 line | Statement: [Istanbul Metro, hasLine, M15 line]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: M15 line Context triple: [Istanbul Metro, hasLine, M15 line]
-
A.
M11 line
The M11 line is a rapid transit route of the Istanbul Metro system that connects the city center with Istanbul Airport and other northern districts.
-
B.
M14 line
The M14 line is a metro line within the Istanbul Metro rapid transit network in Istanbul, Turkey.
-
C.
M1 line
The M1 line is a light metro route in Lausanne, Switzerland, connecting the city center with the university and lakeside areas as part of the Lausanne Métro network.
-
D.
M1 line
The M1 line is one of the main rapid transit routes of the Istanbul Metro, connecting central districts with key transport hubs such as the airport and intercity bus terminal.
-
E.
M1 line
The M1 line is a primary rapid transit route of the Ankara Metro system serving key districts of Turkey’s capital 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: M15 line Triple: [Istanbul Metro, hasLine, M15 line]
Generated description
The M15 line is a rapid transit route within the Istanbul Metro system that serves as part of the city's urban rail network.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: M15 line Target entity description: The M15 line is a rapid transit route within the Istanbul Metro system that serves as part of the city's urban rail network.
-
A.
M11 line
The M11 line is a rapid transit route of the Istanbul Metro system that connects the city center with Istanbul Airport and other northern districts.
-
B.
M14 line
chosen
The M14 line is a metro line within the Istanbul Metro rapid transit network in Istanbul, Turkey.
-
C.
M1 line
The M1 line is a light metro route in Lausanne, Switzerland, connecting the city center with the university and lakeside areas as part of the Lausanne Métro network.
-
D.
M1 line
The M1 line is one of the main rapid transit routes of the Istanbul Metro, connecting central districts with key transport hubs such as the airport and intercity bus terminal.
-
E.
M1 line
The M1 line is a primary rapid transit route of the Ankara Metro system serving key districts of Turkey’s capital city.
- F. None of above.
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_69c68889a2748190a316c5e65360361a |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e88ec6a8819083cbc3f4c39b8c79 |
completed | March 27, 2026, 8:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8342a44a08190abee47cc7482c757 |
completed | March 28, 2026, 8:03 p.m. |
| NEDg | Description generation | batch_69c835904be081908fa9317eb5568d82 |
completed | March 28, 2026, 8:09 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c83621b32c8190bd4b289b5f9f1764 |
completed | March 28, 2026, 8:12 p.m. |
Created at: March 27, 2026, 2:48 p.m.