Triple
T33116801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hairatan border crossing |
E847479
|
entity |
| Predicate | hasOppositeBorderPoint |
P174246
|
FINISHED |
| Object | Termez |
—
|
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: Termez | Statement: [Hairatan border crossing, hasOppositeBorderPoint, Termez]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOppositeBorderPoint Context triple: [Hairatan border crossing, hasOppositeBorderPoint, Termez]
-
A.
hasOppositeComponent
Indicates that one component is related to another as its opposite or contrasting counterpart within a system or structure.
-
B.
hasBoundaryPoint
Indicates that one entity includes a point that lies on the boundary of another entity.
-
C.
hasBorderCheckpointOnOtherSide
chosen
Indicates that a border checkpoint is located on the opposite side of a boundary relative to a referenced point or entity.
-
D.
hasBorderDirection
Indicates that one entity’s border lies in, or is oriented toward, a specified cardinal or relative direction with respect to another entity.
-
E.
liesOnBorderOf
Indicates that one entity is located along or directly adjacent to the boundary line separating it from another entity.
- 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_69f3495751a081909850af5843da40dc |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f9fd6834cc8190aa27153d6a99f3bb |
completed | May 5, 2026, 2:23 p.m. |
| PD | Predicate disambiguation | batch_69f7cf769338819092a5f42653dcc956 |
completed | May 3, 2026, 10:43 p.m. |
Created at: May 1, 2026, 1:27 a.m.