Triple
T1111668
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xhosa |
E11008
|
entity |
| Predicate | clickType |
P24466
|
FINISHED |
| Object | dental clicks |
—
|
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: dental clicks | Statement: [Xhosa, clickType, dental clicks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: clickType Context triple: [Xhosa, clickType, dental clicks]
-
A.
interactionPoint
Indicates a specific location or moment where two or more entities come into contact or engage with each other.
-
B.
captureType
Indicates the manner or method by which something is captured, recorded, or acquired in the context of the relationship.
-
C.
linkType
Indicates the specific kind or category of relationship that connects two linked entities.
-
D.
kitType
Indicates the specific category or configuration of a kit associated with an entity or activity.
-
E.
crossType
Indicates a relationship where one entity intersects, passes over, or traverses another, typically implying movement or extension across a boundary, area, or medium.
- F. None of above. chosen
Provenance (4 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_69a493252a648190ac48f8742474a5e8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4bbd92a8c8190a16e55f3f739010f |
completed | March 1, 2026, 10:21 p.m. |
| PD | Predicate disambiguation | batch_69a4bb42990c819080db96478fd4977e |
completed | March 1, 2026, 10:18 p.m. |
| PDg | Predicate description generation | batch_69a4bbd7ff1881908c943ecdfea59e81 |
completed | March 1, 2026, 10:21 p.m. |
Created at: March 1, 2026, 7:43 p.m.