Triple
T4011852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | African Veldt |
E90661
|
entity |
| Predicate | typicalBarrierType |
P53911
|
FINISHED |
| Object | moats |
—
|
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: moats | Statement: [African Veldt, typicalBarrierType, moats]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalBarrierType Context triple: [African Veldt, typicalBarrierType, moats]
-
A.
typicalStallType
Indicates the usual or most common type or category of stall associated with an entity.
-
B.
guidewayType
Indicates the specific kind or classification of guideway used in a transportation or movement system.
-
C.
ridgeType
Indicates the specific morphological or structural category that a ridge belongs to within a classification of ridge forms.
-
D.
crossingType
Indicates the specific kind or category of crossing (e.g., how or where one thing passes over, through, or across another).
-
E.
fortType
Indicates the specific kind or classification of a fort associated with an entity.
- 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_69aed95e44088190aff7d90a151b1b20 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefaec08dc8190a341809059554f84 |
completed | March 9, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_69aef8fa6fec81909b1190ecbba61410 |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aefaea76c48190add2e7cee180e8b1 |
completed | March 9, 2026, 4:52 p.m. |
Created at: March 9, 2026, 3:34 p.m.