Triple
T5550196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iranun |
E145506
|
entity |
| Predicate | countryStatusInPhilippines |
P33447
|
FINISHED |
| Object | recognized minority language |
—
|
LITERAL 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: recognized minority language | Statement: [Iranun, countryStatusInPhilippines, recognized minority language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryStatusInPhilippines Context triple: [Iranun, countryStatusInPhilippines, recognized minority language]
-
A.
rankByAreaInPhilippines
Indicates the relative ordering of entities based on their area size specifically within the Philippines.
-
B.
countryStatus
Indicates the political or legal condition of a country, such as its sovereignty, recognition, or current state in international or domestic contexts.
-
C.
countrySpecificStatus
chosen
Indicates a status or condition that is defined or applied specifically in the context of a particular country.
-
D.
regionStatus
Indicates the current condition, classification, or operational state assigned to a specific geographic or administrative region.
-
E.
GIStatusCountry
Indicates the status or condition of a geographic indication (GI) within a specific country.
- F. None of above.
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_69c008fb879c81909f5bfa56fadc1d46 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01fe2aef481909944bc582c1f67a4 |
completed | March 22, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69c01b0e72f08190bf705d8fe1639401 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:35 p.m.