Triple
T13456434
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Türkmenabat–Kerki line |
E311245
|
entity |
| Predicate | connects |
P390
|
FINISHED |
| Object | Kerki |
E1033058
|
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: Kerki | Statement: [Türkmenabat–Kerki line, connects, Kerki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kerki Context triple: [Türkmenabat–Kerki line, connects, Kerki]
-
A.
Kerki
chosen
Kerki is a town in eastern Turkmenistan situated on the Amu Darya River, historically known as a regional trading and transport hub.
-
B.
Keratea
Keratea is a town in eastern Attica, Greece, known for its historical significance and proximity to the Athens metropolitan area.
-
C.
Kerkebet
Kerkebet is a small town in the Anseba region of Eritrea.
-
D.
Kerria
Kerria is a small genus of deciduous flowering shrubs, best known for the ornamental Japanese kerria with its bright yellow, rose-like blooms.
-
E.
Karesi
Karesi is a central district and municipality of Balıkesir in western Turkey, known for its role as an administrative and commercial hub of the province.
- 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_69d806a938b8819097ec43a2229fc7f9 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf0a75008190a508060c85f73604 |
completed | April 12, 2026, 2:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7399e33008190b10c14f30ff0c0d2 |
completed | May 3, 2026, 12:03 p.m. |
Created at: April 9, 2026, 9:41 p.m.