Triple
T2054301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Binisaya |
E45639
|
entity |
| Predicate | alternativeName |
P39
|
FINISHED |
| Object | Bisaya |
E45639
|
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: Bisaya | Statement: [Binisaya, alternativeName, Bisaya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bisaya Context triple: [Binisaya, alternativeName, Bisaya]
-
A.
Binisaya
chosen
Binisaya is a major Austronesian language of the Philippines, widely spoken in the Central Visayas and parts of Mindanao.
-
B.
Waray language
Waray is an Austronesian language spoken primarily in the Eastern Visayas region of the Philippines, particularly on Samar and nearby islands.
-
C.
Butuanon language
The Butuanon language is an Austronesian language spoken primarily in and around Butuan City in Mindanao, Philippines.
-
D.
Winaray
Winaray is an Austronesian language spoken primarily in the Eastern Visayas region of the Philippines, particularly in Samar, northern Leyte, and nearby areas.
-
E.
Bislama
Bislama is an English-based creole language widely spoken in Vanuatu and used as a key lingua franca across its many islands and communities.
- 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_69a8891a19508190a12ef1e192308dcb |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb9a8518081909ba95a8ef9321f12 |
completed | March 7, 2026, 5:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae200eb09881908bbfe47ebb62f55e |
completed | March 9, 2026, 1:19 a.m. |
Created at: March 4, 2026, 7:39 p.m.