Triple
T19898795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cagayan Province |
E478223
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Allacapan |
—
|
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: Allacapan | Statement: [Cagayan Province, hasMunicipality, Allacapan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Allacapan Context triple: [Cagayan Province, hasMunicipality, Allacapan]
-
A.
Allacapan
chosen
Allacapan is a rural municipality in the province of Cagayan in the Cagayan Valley region of the Philippines.
-
B.
Malibcong
Malibcong is a remote, mountainous municipality in the Philippine province of Abra known for its indigenous communities and largely undeveloped natural landscapes.
-
C.
Mamanguape
Mamanguape is a municipality in the Brazilian state of Paraíba, known for its historical colonial architecture and location near the Mamanguape River on the state’s northern coast.
-
D.
Palawano
Palawano is an Austronesian language spoken by the indigenous Palawano people of Palawan in the Philippines.
-
E.
Pilcaniyeu
Pilcaniyeu is a small town in Argentina’s Patagonia region, located in the Andean area of Río Negro Province and known for its rural character and nearby natural landscapes.
- 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_69d8e520682081909892916424699bd5 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6593fbb348190afa7acf45af406ed |
completed | April 20, 2026, 4:50 p.m. |
Created at: April 10, 2026, 1:52 p.m.