Triple
T11964517
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ilonggo people |
E284757
|
entity |
| Predicate | nativeName |
P15
|
FINISHED |
| Object | Mga Ilonggo |
E58819
|
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: Mga Ilonggo | Statement: [Ilonggo people, nativeName, Mga Ilonggo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mga Ilonggo Context triple: [Ilonggo people, nativeName, Mga Ilonggo]
-
A.
Ilonggo
chosen
Ilonggo is a major Austronesian language spoken primarily in Western Visayas and parts of Mindanao in the Philippines.
-
B.
Sasmuan
Sasmuan is a coastal municipality in the province of Pampanga in the Philippines, known for its fishing industry, wetlands, and bird-watching sites.
-
C.
Ibanag
Ibanag is an Austronesian language spoken primarily in the Cagayan Valley region of northern Luzon in the Philippines.
-
D.
Tagoloan
Tagoloan is a coastal municipality in Misamis Oriental, Philippines, known for its strategic location near Cagayan de Oro and its growing industrial and port activities.
-
E.
Malabanias
Malabanias is a barangay (village-level administrative district) within Angeles City in Pampanga, Philippines, known for its mixed residential, commercial, and entertainment areas.
- 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_69d6ab2eaeb881909f7914758f859413 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903799f948190a5dc4d3822f3ff27 |
completed | April 10, 2026, 2:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f471d625c88190baed4ea08853988a |
completed | May 1, 2026, 9:26 a.m. |
Created at: April 8, 2026, 9:45 p.m.