Triple
T645286
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ankara |
E11226
|
entity |
| Predicate | hasMetroSystem |
P522
|
FINISHED |
| Object |
Ankara Metro
Ankara Metro is the rapid transit system serving Turkey's capital city, providing urban rail transportation across Ankara and its surrounding districts.
|
E80644
|
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: Ankara Metro | Statement: [Ankara, hasMetroSystem, Ankara Metro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ankara Metro Context triple: [Ankara, hasMetroSystem, Ankara Metro]
-
A.
Izmir Metro
Izmir Metro is a rapid transit rail system serving the city of Izmir, Turkey, providing high-capacity urban transportation across key districts.
-
B.
Tehran Metro
Tehran Metro is the rapid transit system serving Iran’s capital, providing extensive urban and suburban rail transport across the Tehran metropolitan area.
-
C.
Tram Izmir
Tram Izmir is a modern light rail tram network serving the Turkish city of İzmir as part of its urban public transportation system.
-
D.
Budapest Metro
The Budapest Metro is the rapid transit system serving Hungary’s capital, notable for including Line 1, one of the oldest electrified underground railway lines in continental Europe.
-
E.
Turin Metro
The Turin Metro is a fully automated, driverless rapid transit system serving the city of Turin, Italy.
- 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: Ankara Metro Triple: [Ankara, hasMetroSystem, Ankara Metro]
Generated description
Ankara Metro is the rapid transit system serving Turkey's capital city, providing urban rail transportation across Ankara and its surrounding districts.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ankara Metro Target entity description: Ankara Metro is the rapid transit system serving Turkey's capital city, providing urban rail transportation across Ankara and its surrounding districts.
-
A.
Izmir Metro
Izmir Metro is a rapid transit rail system serving the city of Izmir, Turkey, providing high-capacity urban transportation across key districts.
-
B.
Tehran Metro
Tehran Metro is the rapid transit system serving Iran’s capital, providing extensive urban and suburban rail transport across the Tehran metropolitan area.
-
C.
Tram Izmir
Tram Izmir is a modern light rail tram network serving the Turkish city of İzmir as part of its urban public transportation system.
-
D.
Budapest Metro
The Budapest Metro is the rapid transit system serving Hungary’s capital, notable for including Line 1, one of the oldest electrified underground railway lines in continental Europe.
-
E.
Turin Metro
The Turin Metro is a fully automated, driverless rapid transit system serving the city of Turin, Italy.
- 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_69a493266a2881909daf4c40f719dee8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49f19f9a08190b0bf6e19b32427ff |
completed | March 1, 2026, 8:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a57b5a0c0c81909aa3339d7ba62a0d |
completed | March 2, 2026, 11:58 a.m. |
| NEDg | Description generation | batch_69a57dbf6b1c8190981f9d85f721a7db |
completed | March 2, 2026, 12:08 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a57e2762908190957f71686d107483 |
completed | March 2, 2026, 12:10 p.m. |
Created at: March 1, 2026, 7:36 p.m.