Triple
T19269865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Capiceño |
E481892
|
entity |
| Predicate | hasNativeName |
P1435
|
FINISHED |
| Object | Bisaya nga Capisnon |
—
|
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: Bisaya nga Capisnon | Statement: [Capiceño, hasNativeName, Bisaya nga Capisnon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bisaya nga Capisnon Context triple: [Capiceño, hasNativeName, Bisaya nga Capisnon]
-
A.
Binisaya nga Capisnon
chosen
Binisaya nga Capisnon is a regional Visayan language spoken primarily in the province of Capiz in the Philippines.
-
B.
Surigaonon Bisaya
Surigaonon Bisaya is a Visayan language variety spoken primarily in Surigao and nearby areas in the northeastern part of Mindanao in the Philippines.
-
C.
Bayan ng Poro
Bayan ng Poro is a municipality in the province of Cebu in the Philippines, located on Poro Island in the Camotes Sea.
-
D.
Bacoleña
Bacoleña is the Spanish-derived demonym referring to a female resident or native of Bacolor, a municipality in the Philippines.
-
E.
Agutaynon
Agutaynon is an Austronesian language spoken by the Agutaynon people, primarily on Agutaya Island in the Philippines.
- 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_69d8e8ce54cc8190998418ff1f66ef28 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fbb74ec48190a58d96b4b5b9af00 |
completed | April 20, 2026, 10:11 a.m. |
Created at: April 10, 2026, 1:29 p.m.