Triple
T15548510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M37 highway |
E370675
|
entity |
| Predicate | connects |
P390
|
FINISHED |
| Object | Türkmenbaşy |
E529394
|
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: Türkmenbaşy | Statement: [M37 highway, connects, Türkmenbaşy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Türkmenbaşy Context triple: [M37 highway, connects, Türkmenbaşy]
-
A.
Türkmenbaşy
chosen
Türkmenbaşy is a port city in western Turkmenistan on the Caspian Sea, serving as a key hub for maritime trade and regional transport.
-
B.
Türkmenabat
Türkmenabat is a major city in eastern Turkmenistan, serving as an important industrial, transport, and agricultural center near the border with Uzbekistan.
-
C.
Temirtau
Temirtau is a major industrial city in Kazakhstan, best known for its large steel production complex and heavy metallurgical industry.
-
D.
Bazar-Korgon
Bazar-Korgon is a town in southwestern Kyrgyzstan, known as a local administrative and market center in the Jalal-Abad Region.
-
E.
Akçaabat
Akçaabat is a coastal town and district in Turkey’s Trabzon Province on the Black Sea, known for its historic architecture and distinctive local cuisine.
- 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_69d85cc6cf40819091f4a5facee1ebe6 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04a93121881909d88ca55a39252ac |
completed | April 16, 2026, 2:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff455c172c8190833274cb98667e84 |
completed | May 9, 2026, 2:31 p.m. |
Created at: April 10, 2026, 4:08 a.m.