Triple
T22215426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colombo Port City development |
E549061
|
entity |
| Predicate | economicIncentives |
P7916
|
FINISHED |
| Object | tax concessions |
—
|
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: tax concessions | Statement: [Colombo Port City development, economicIncentives, tax concessions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: economicIncentives Context triple: [Colombo Port City development, economicIncentives, tax concessions]
-
A.
providesIncentivesTo
Indicates that one entity offers rewards, benefits, or motivations to another entity to encourage a desired behavior or outcome.
-
B.
providedTaxIncentivesForSavings
Indicates that an authority or organization granted tax benefits to encourage individuals or entities to save money.
-
C.
stateIncentives
Indicates that a state government provides benefits, subsidies, or other inducements to encourage a particular action, behavior, or investment.
-
D.
economicPolicyType
Indicates the classification of an economic policy according to its general type or category (e.g., fiscal, monetary, trade).
-
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_69e11e3f7e04819089806d81d5ac431e |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12b8bdfbc8190832809edbe8b7c27 |
completed | April 28, 2026, 9:50 p.m. |
| PD | Predicate disambiguation | batch_69e71b4dcc408190a30429fb08fcf39e |
completed | April 21, 2026, 6:38 a.m. |
Created at: April 16, 2026, 8:37 p.m.