Triple
T27823616
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Turkish national road network |
E702886
|
entity |
| Predicate | linksToNeighboringCountry |
P105151
|
FINISHED |
| Object | Greece |
—
|
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: Greece | Statement: [Turkish national road network, linksToNeighboringCountry, Greece]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linksToNeighboringCountry Context triple: [Turkish national road network, linksToNeighboringCountry, Greece]
-
A.
connectsToCountryBorder
Indicates that one entity is directly adjacent to and touches the border of a specified country.
-
B.
borderingCountryConnectivity
Indicates that two countries share a land or maritime border that allows direct movement or interaction between them.
-
C.
linksCountry
Indicates a relationship where one entity connects or associates another entity specifically with a country.
-
D.
crossBorderLinks
chosen
Indicates connections or interactions that extend across or link entities in different geographic or political jurisdictions.
-
E.
neighboringCountryPresence
Indicates that one country has a geographic presence (such as territory, bases, or influence) in or immediately adjacent to a neighboring country.
- F. None of above.
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_69ef840ad1e88190b5bff2d1ddec8700 |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f64dbbaefc8190952b8320bf4397d8 |
completed | May 2, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69f64cacd2c08190aed8a1761d0da679 |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 27, 2026, 5:50 p.m.