Triple
T27903596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Telangana–Maharashtra border |
E705705
|
entity |
| Predicate | hasCheckpostType |
P19385
|
FINISHED |
| Object | interstate commercial tax checkposts |
—
|
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: interstate commercial tax checkposts | Statement: [Telangana–Maharashtra border, hasCheckpostType, interstate commercial tax checkposts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCheckpostType Context triple: [Telangana–Maharashtra border, hasCheckpostType, interstate commercial tax checkposts]
-
A.
hasCheckpointType
chosen
Indicates that a checkpoint is associated with a specific type or category defining its role or characteristics.
-
B.
hasIntegratedCheckPost
Indicates that one entity includes or contains a check post that is functionally integrated within it.
-
C.
hasCheckoutType
Indicates the type or method of checkout associated with a given transaction or entity.
-
D.
haveType
Indicates that an entity belongs to or is classified under a specified type or category.
-
E.
hasCheckInCategory
Indicates that an entity is associated with a specific category or type of check-in event.
- 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_69ef96b490ac8190a412d04c5d009f3e |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f7117e55908190a67105e92bc4830f |
completed | May 3, 2026, 9:12 a.m. |
| PD | Predicate disambiguation | batch_69f70f380690819090cc34763ba460ed |
completed | May 3, 2026, 9:02 a.m. |
Created at: April 27, 2026, 6:43 p.m.