Triple
T18986702
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eastern Province |
E464575
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Ampara |
—
|
NE NERFINISHED |
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: Ampara | Statement: [Eastern Province, hasCity, Ampara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ampara Context triple: [Eastern Province, hasCity, Ampara]
-
A.
Ampara
chosen
Ampara is a major town in Sri Lanka known as an agricultural and administrative center in the island’s Eastern Province.
-
B.
Łukta
Łukta is a village in northern Poland located in the Warmian-Masurian Voivodeship, known for its proximity to the region’s lakes and forests.
-
C.
Kalutara
Kalutara is a major coastal town in western Sri Lanka, known for its historic Buddhist temple, scenic beaches, and role as a regional commercial hub.
-
D.
Pangkajene
Pangkajene is a town in South Sulawesi, Indonesia, serving as the administrative and economic center of the Pangkajene and Islands Regency.
-
E.
Sapopemba
Sapopemba is a metro station on São Paulo’s Line 15–Silver monorail, serving the Sapopemba district in the city’s eastern zone.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dd008af48190a97ff1c6488edf1b |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d660835c8190bedd78590b3e0a7e |
completed | April 20, 2026, 7:31 a.m. |
Created at: April 10, 2026, 12:01 p.m.