Triple
T37787631
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baku–Tbilisi–Ceyhan pipeline |
E941995
|
entity |
| Predicate | avoidsTransitCountry |
P189217
|
FINISHED |
| Object | Russia |
—
|
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: Russia | Statement: [Baku–Tbilisi–Ceyhan pipeline, avoidsTransitCountry, Russia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: avoidsTransitCountry Context triple: [Baku–Tbilisi–Ceyhan pipeline, avoidsTransitCountry, Russia]
-
A.
passesThroughCountry
Indicates that a route, path, or object traverses or crosses within the boundaries of a specified country.
-
B.
nonSchengenCountryAtPoint
Indicates that a given location lies within the territory of a country that is not part of the Schengen Area at that point.
-
C.
viaCountry
Indicates that something passes through, transits, or is routed by way of a specified country.
-
D.
associatedWithDepartureCountry
Indicates that there is a relationship linking something (such as a person, object, or event) to the country from which a departure takes place.
-
E.
supportsNonSchengenFlights
Indicates that the subject facility or service is capable of handling or accommodating flights that operate outside the Schengen Area.
- F. None of above. chosen
Provenance (4 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_69f76ee5cb0c81909a363d1c929156c0 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbb9e8108c8190ae1c7940b1677e95 |
completed | May 6, 2026, 10 p.m. |
| PD | Predicate disambiguation | batch_69fbb141605c8190b9c27d70352522db |
completed | May 6, 2026, 9:23 p.m. |
| PDg | Predicate description generation | batch_69fbb9e69b7481909beaf8264d87c5e5 |
completed | May 6, 2026, 10 p.m. |
Created at: May 3, 2026, 4:19 p.m.