Triple

T26840673
Position Surface form Disambiguated ID Type / Status
Subject Coimbatore SEZ E675766 entity
Predicate regulatoryIncentive P7916 FINISHED
Object single-window clearance 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: single-window clearance | Statement: [Coimbatore SEZ, regulatoryIncentive, single-window clearance]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: regulatoryIncentive
Context triple: [Coimbatore SEZ, regulatoryIncentive, single-window clearance]
  • A. providesIncentivesTo
    Indicates that one entity offers rewards, benefits, or motivations to another entity to encourage a desired behavior or outcome.
  • B. regulatoryAdvantage
    Indicates that one entity gains a favorable position or benefit over others due to laws, rules, or regulatory conditions.
  • C. regulatesIn
    Indicates that one entity controls, modulates, or influences the activity, expression, or behavior of another entity within a system or process.
  • D. stateIncentives
    Indicates that a state government provides benefits, subsidies, or other inducements to encourage a particular action, behavior, or investment.
  • E. typeOfIncentive chosen
    Indicates the specific kind or category of incentive associated with an entity or action.
  • 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_69f6fb19063c81909466b329655c8583 completed May 3, 2026, 7:36 a.m.
PD Predicate disambiguation batch_69f6f969b4cc8190afb473a2d8b110bc completed May 3, 2026, 7:29 a.m.
Created at: April 27, 2026, 5:07 a.m.