Triple
T13251159
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M1 line |
E315531
|
entity |
| Predicate | isUndergroundIn |
P10157
|
FINISHED |
| Object | central Ankara |
E301865
|
NE FINISHED |
How this triple was built (2 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: central Ankara | Statement: [M1 line, isUndergroundIn, central Ankara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: central Ankara Context triple: [M1 line, isUndergroundIn, central Ankara]
-
A.
Ankara
Ankara is the political and administrative center of Turkey, known for hosting the country’s government institutions and foreign embassies.
-
B.
Ankara Metropolitan Municipality
Ankara Metropolitan Municipality is the primary local government authority responsible for administering and providing public services across Turkey’s capital city, Ankara.
-
C.
Kayseri
Kayseri is a historic city in central Turkey, known for its Seljuk and Ottoman architectural heritage and its role as a major commercial and cultural center in Anatolia.
-
D.
Etimesgut
Etimesgut is a rapidly growing suburban district and municipality on the western side of Ankara, Turkey’s capital city.
-
E.
Çankaya
chosen
Çankaya is a central district of Ankara, Turkey, known for housing key government institutions, foreign embassies, and major national landmarks.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d806b1072881909e46bd212259c5f0 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98f73423c8190932a9edac56df383 |
completed | April 11, 2026, 12:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f70a3b8ca48190863aff25f12d0e7e |
completed | May 3, 2026, 8:41 a.m. |
Created at: April 9, 2026, 9:24 p.m.