Triple
T26840685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coimbatore SEZ |
E675766
|
entity |
| Predicate | hasIncentiveType |
P7916
|
FINISHED |
| Object | fiscal incentives |
—
|
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: fiscal incentives | Statement: [Coimbatore SEZ, hasIncentiveType, fiscal incentives]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIncentiveType Context triple: [Coimbatore SEZ, hasIncentiveType, fiscal incentives]
-
A.
typeOfIncentive
chosen
Indicates the specific kind or category of incentive associated with an entity or action.
-
B.
usesIncentive
Indicates that one entity employs or applies an incentive (such as a reward, benefit, or motivation) to influence the behavior or decisions of another entity.
-
C.
offersIncentive
Indicates that one entity provides a reward, benefit, or motivation to another entity to encourage a specific action or behavior.
-
D.
hasBenefitType
Indicates that an entity is associated with a specific category or type of benefit it provides or receives.
-
E.
providesIncentivesTo
Indicates that one entity offers rewards, benefits, or motivations to another entity to encourage a desired behavior or outcome.
- 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_69eee9b8d5e88190a07d3455c0fbb21f |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69fcd867f36081908c88c55a6a1404c1 |
completed | May 7, 2026, 6:22 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f47b188190b4cf4b4c748d9d03 |
completed | May 7, 2026, 5:55 p.m. |
Created at: April 27, 2026, 5:07 a.m.