Triple
T2495090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swat Valley |
E52135
|
entity |
| Predicate | hasApproxArea |
P20336
|
FINISHED |
| Object | about 5,000 square kilometers |
—
|
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: about 5,000 square kilometers | Statement: [Swat Valley, hasApproxArea, about 5,000 square kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproxArea Context triple: [Swat Valley, hasApproxArea, about 5,000 square kilometers]
-
A.
areaApprox
Indicates that one entity’s area is approximately equal to the area of another entity.
-
B.
hasDimensionsApprox
Indicates that an entity has physical dimensions that are known only approximately, rather than as exact measurements.
-
C.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
D.
hasApproximateExtent
chosen
Indicates that one entity has a spatial, temporal, or quantitative extent that is only roughly or approximately specified rather than exact.
-
E.
hasApproximateCoordinates
Indicates that an entity is associated with location coordinates that are estimated or imprecise rather than exact.
- 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_69ab4955111c8190835bf619adec21ff |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd19541048190b9e39db119c20fe8 |
completed | March 7, 2026, 7:19 a.m. |
| PD | Predicate disambiguation | batch_69abd0b980b481908d4932bcea4a6167 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:45 p.m.