Triple
T7767119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hatay Province |
E178976
|
entity |
| Predicate | borderLengthWithSyria |
P57957
|
FINISHED |
| Object | approximately 230 km |
—
|
LITERAL 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: approximately 230 km | Statement: [Hatay Province, borderLengthWithSyria, approximately 230 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderLengthWithSyria Context triple: [Hatay Province, borderLengthWithSyria, approximately 230 km]
-
A.
distanceFromSyriaBorder
Indicates the measured spatial separation between a location and the nearest point on Syria’s national border.
-
B.
borderTypeWithYemen
Indicates the type or nature of the border that exists between a given entity and Yemen.
-
C.
lostLastTerritoryInSyria
Indicates that the entity ceased to control its final remaining territorial holding within Syria.
-
D.
shareLandBorderLengthApproxKm
chosen
Indicates that two entities share a land border whose length is approximately the given number of kilometers.
-
E.
distanceToLebanonBorder
Indicates the measured or estimated spatial distance between a given location and the border of Lebanon.
- 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_69c69f30602c819082ab52cd4af5c592 |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c7043451bc8190a76ee066b779b7d7 |
completed | March 27, 2026, 10:27 p.m. |
| PD | Predicate disambiguation | batch_69c7016f4ce881909c2e9f610255187b |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:11 p.m.