Triple
T12982070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Weligama |
E321674
|
entity |
| Predicate | nearbyPlace |
P2064
|
FINISHED |
| Object | Mirissa |
E321675
|
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: Mirissa | Statement: [Weligama, nearbyPlace, Mirissa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mirissa Context triple: [Weligama, nearbyPlace, Mirissa]
-
A.
Mirissa
chosen
Mirissa is a small coastal town in southern Sri Lanka known for its scenic beaches, surfing, and whale-watching opportunities.
-
B.
Maiana
Maiana is a low-lying coral atoll in the central Pacific nation of Kiribati, known for its traditional village life and vulnerability to sea-level rise.
-
C.
Laka
Laka is a dialect of the Sara language spoken in parts of Central Africa, particularly in Chad and neighboring regions.
-
D.
Vai Malandra
"Vai Malandra" is a hit Brazilian funk-pop song by singer Anitta that became a major cultural phenomenon and chart success in Brazil and internationally.
-
E.
Mazunte
Mazunte is a small, laid-back beach town on Mexico’s Oaxacan coast, known for its sea turtle conservation center, eco-tourism, and scenic Pacific shoreline.
- 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_69d8076479b8819090afce3591939cdf |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e5ca33481909a6cb06c636889f9 |
completed | April 10, 2026, 10:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6cbc277c881909ae77e8a44e06986 |
completed | May 3, 2026, 4:14 a.m. |
Created at: April 9, 2026, 8:39 p.m.