Triple
T22230940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ratmalana |
E549463
|
entity |
| Predicate | airportFormerRole |
P4950
|
FINISHED |
| Object | main international airport of Sri Lanka (historical) |
—
|
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: main international airport of Sri Lanka (historical) | Statement: [Ratmalana, airportFormerRole, main international airport of Sri Lanka (historical)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airportFormerRole Context triple: [Ratmalana, airportFormerRole, main international airport of Sri Lanka (historical)]
-
A.
formerAirportType
Indicates that an entity previously had a specific airport classification or type, but no longer holds that status.
-
B.
hasFormerAirport
Indicates that an entity previously had an airport that is no longer in operation or no longer exists.
-
C.
replacedAsMainAirportFor
Indicates that one airport has taken over the role of being the primary or main airport serving a particular area from another airport.
-
D.
formerAirportStatus
chosen
Indicates that an entity previously held the status of an airport but no longer functions as one.
-
E.
airportRole
Indicates that an entity serves a specific functional role or capacity within the context of an airport.
- 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_69e11e4102b881909cf47d3768e25c19 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12bf2a26c81908aaf614d7c75e219 |
completed | April 28, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69e71b5177d881908f90abde14ada7dc |
completed | April 21, 2026, 6:38 a.m. |
Created at: April 16, 2026, 8:37 p.m.