Triple
T33342410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kongo languages |
E853705
|
entity |
| Predicate | regionOfHighConcentration |
P70368
|
FINISHED |
| Object | Lower Congo region |
—
|
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: Lower Congo region | Statement: [Kongo languages, regionOfHighConcentration, Lower Congo region]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionOfHighConcentration Context triple: [Kongo languages, regionOfHighConcentration, Lower Congo region]
-
A.
hasPopulationConcentrationIn
chosen
Indicates that a population is densely or significantly clustered within a specified geographic area or region.
-
B.
occupiedRegion
Indicates that an entity has taken control of and is currently holding a specific geographic area or region.
-
C.
largestConcentrationIn
Indicates that something has its highest density, amount, or presence within a specified location or group compared to all other locations or groups.
-
D.
hasCoordinateConcentration
Indicates that an entity has a specific concentration value associated with a particular spatial or coordinate location.
-
E.
hasHighDensityOf
Indicates that one entity contains or exhibits a large concentration or amount of another entity within a given area, volume, or context.
- 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_69f3496a1a588190bad9cbe9221144e0 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff255b84788190a94682f4efe1d0b8 |
completed | May 9, 2026, 12:15 p.m. |
| PD | Predicate disambiguation | batch_69ff24f3ab108190bb017a656cff3d82 |
completed | May 9, 2026, 12:13 p.m. |
Created at: May 1, 2026, 1:34 a.m.