Triple
T30496434
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hadariba |
E776018
|
entity |
| Predicate | geographicalProximityTo |
P55639
|
FINISHED |
| Object | Beni-Amir people |
—
|
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: Beni-Amir people | Statement: [Hadariba, geographicalProximityTo, Beni-Amir people]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: geographicalProximityTo Context triple: [Hadariba, geographicalProximityTo, Beni-Amir people]
-
A.
nearbyTo
Indicates that one entity is located close in distance or position to another entity.
-
B.
featuresRegionalProximity
chosen
Indicates that one entity is located near or in close geographic proximity to a particular region or another entity.
-
C.
proximityToLandmark
Indicates a spatial relationship where one entity is located near or close to a specified landmark.
-
D.
isNearCapitalCity
Indicates that an entity is located close to, or in the immediate vicinity of, a capital city.
-
E.
hasNearbyGeographicalArea
Indicates that one geographical area is located in close spatial proximity to another geographical area.
- 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_69f22498c5d481908aaea89e6fab8280 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f71f8ee0688190bd025f27993452d3 |
completed | May 3, 2026, 10:12 a.m. |
| PD | Predicate disambiguation | batch_69f71cc405c08190863565609a4c8499 |
completed | May 3, 2026, 10 a.m. |
Created at: April 29, 2026, 8:14 p.m.