Triple
T14128389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Koggala |
E340092
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Ahangama |
E323362
|
NE 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: Ahangama | Statement: [Koggala, near, Ahangama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ahangama Context triple: [Koggala, near, Ahangama]
-
A.
Ahangama
chosen
Ahangama is a coastal town in southern Sri Lanka known for its beaches, surfing spots, and traditional stilt fishermen.
-
B.
Marangona
Marangona is the largest and most famous bell of St Mark's Campanile in Venice, traditionally used to mark the beginning and end of the working day and to signal important civic events.
-
C.
Sikaiana
Sikaiana is a small, remote Polynesian atoll in the Solomon Islands whose people and culture are part of the Polynesian outlier communities in Melanesia.
-
D.
Nganzai
Nganzai is a local government area in Borno State, northeastern Nigeria, known for its rural communities and impact from the Boko Haram insurgency.
-
E.
Mangini
Mangini is an Italian surname most notably associated with former NFL head coach and analyst Eric Mangini.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d81c6a95b481909e39111e0c1f31ee |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de6098013c8190b1bac9d3fff60acd |
completed | April 14, 2026, 3:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcdf0ed0a88190a7126887364fccdd |
completed | May 7, 2026, 6:50 p.m. |
Created at: April 9, 2026, 10:22 p.m.