Triple
T28458329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lodha |
E716778
|
entity |
| Predicate | associatedWithForestAreasOf |
P128550
|
FINISHED |
| Object | West Bengal |
—
|
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: West Bengal | Statement: [Lodha, associatedWithForestAreasOf, West Bengal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithForestAreasOf Context triple: [Lodha, associatedWithForestAreasOf, West Bengal]
-
A.
hasForestAssociation
chosen
Indicates an ecological or contextual relationship in which an entity is associated with, influenced by, or characteristically occurs in forest environments.
-
B.
associatedWithWildlifeArea
Indicates that an entity has a connection, involvement, or linkage with a designated wildlife area.
-
C.
notableForestAreas
Indicates that there exists a forested region associated with the subject that is recognized as significant or noteworthy in some context.
-
D.
forestArea
Indicates the extent or size of land covered by forest within a given area or region.
-
E.
partOfForestRegion
Indicates that one entity is a component or subdivision within a larger forest region.
- 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_69efd6b76f8c8190a7ba908aca280942 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_6a015ff02814819094806517fc4c69fa |
completed | May 11, 2026, 4:49 a.m. |
| PD | Predicate disambiguation | batch_6a0154ddd3c48190b85f9f48731cfd8f |
completed | May 11, 2026, 4:02 a.m. |
Created at: April 28, 2026, 1:55 a.m.