Triple
T30857614
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kopet Dag (region) |
E785969
|
entity |
| Predicate | naturalFrontierBetween |
P39423
|
FINISHED |
| Object | Iran |
—
|
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: Iran | Statement: [Kopet Dag (region), naturalFrontierBetween, Iran]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: naturalFrontierBetween Context triple: [Kopet Dag (region), naturalFrontierBetween, Iran]
-
A.
frontierWith
Indicates that two regions or territories share a common boundary or border, especially one marking the edge of settled or controlled area.
-
B.
wasFrontierBetween
Indicates that one entity historically served as the boundary or border region separating two other entities.
-
C.
boundaryBetween
chosen
Indicates that something serves as a dividing line or limit separating two distinct regions, areas, or entities.
-
D.
nearBorderBetween
Indicates that something is located close to the dividing line or boundary shared between two adjacent areas or regions.
-
E.
frontLineBetween
Indicates that a boundary or line of direct confrontation exists separating two opposing sides or regions.
- 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_69f224b91c14819084e764832fe67a57 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6abaa1f648190b77073771df3bf3b |
completed | May 3, 2026, 1:58 a.m. |
| PD | Predicate disambiguation | batch_69f6aa1e84b88190b025f6ca40f17a8a |
completed | May 3, 2026, 1:51 a.m. |
Created at: April 29, 2026, 8:46 p.m.