Triple
T30789075
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warud |
E784039
|
entity |
| Predicate | hasFruitBelt |
P108713
|
FINISHED |
| Object | orange belt of Vidarbha |
—
|
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: orange belt of Vidarbha | Statement: [Warud, hasFruitBelt, orange belt of Vidarbha]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFruitBelt Context triple: [Warud, hasFruitBelt, orange belt of Vidarbha]
-
A.
hasPhysicalBelt
chosen
Indicates that one entity possesses or is equipped with a physical belt as an item or feature.
-
B.
hasCommuterBelt
Indicates that one area functions as the commuter belt for another, meaning people regularly travel from the first area to the second for work or daily activities.
-
C.
usesBeltSystem
Indicates that a subject employs a structured belt-ranking system (e.g., colored belts) to denote levels of skill, progress, or status.
-
D.
hasFruitType
Indicates that an entity possesses or is associated with a specific type or category of fruit.
-
E.
hasConveyorBeltTo
Indicates that one location, machine, or area is connected to another by a conveyor belt that transports items between them.
- 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_69f224b2e2a48190b19aa43db9da5b67 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f707f7959881908f037f0d6b1d0c36 |
completed | May 3, 2026, 8:31 a.m. |
| PD | Predicate disambiguation | batch_69f700fc274c8190a128593dc7c7abd0 |
completed | May 3, 2026, 8:02 a.m. |
Created at: April 29, 2026, 8:41 p.m.