Triple
T18172803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toyota C-HR |
E435073
|
entity |
| Predicate | assemblyLocation |
P40
|
FINISHED |
| Object | TMMT Sakarya, Turkey |
—
|
NE NERFINISHED |
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: TMMT Sakarya, Turkey | Statement: [Toyota C-HR, assemblyLocation, TMMT Sakarya, Turkey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TMMT Sakarya, Turkey Context triple: [Toyota C-HR, assemblyLocation, TMMT Sakarya, Turkey]
-
A.
Sakarya, Turkey
chosen
Sakarya, Turkey is an industrial and agricultural province in northwestern Turkey, known for its automotive manufacturing plants and strategic location near Istanbul.
-
B.
Sari, Turkey
Sari, Turkey is a town and district in Erzurum Province in Eastern Anatolia, known for its rural character and high-altitude, continental climate.
-
C.
SUNTURK
SUNTURK is the radio callsign used by Pegasus Airlines for air traffic control communications.
-
D.
Savur, Mardin, Turkey
Savur is a historic district and town in Turkey’s southeastern Mardin Province, known for its traditional stone architecture and multicultural heritage.
-
E.
Giresun, Turkey
Giresun, Turkey is a Black Sea coastal city in northeastern Turkey known for its hazelnut production and lush, hilly landscape.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b90b7a188190b3fc7b8d4a6cd20a |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4df56d0a88190af3f407d2a3bb74f |
completed | April 19, 2026, 1:57 p.m. |
Created at: April 10, 2026, 10:30 a.m.