Triple
T12504733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cagayan |
E298919
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Aparri |
E430676
|
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: Aparri | Statement: [Cagayan, hasCity, Aparri]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aparri Context triple: [Cagayan, hasCity, Aparri]
-
A.
Aparri
chosen
Aparri is a coastal municipality in the province of Cagayan in the Philippines, known historically as a major port and fishing town at the mouth of the Cagayan River.
-
B.
Nabawan
Nabawan is a rural town and district in the interior of Sabah, Malaysia, known for its indigenous communities and agricultural activities.
-
C.
Pakurumo
Pakurumo is a popular Afrobeat song by Nigerian artist Wizkid, known for its upbeat rhythm and dance-friendly vibe.
-
D.
Parai
Parai is a traditional Tamil frame drum used in folk music, rituals, and social gatherings, often associated with ceremonial and community performances.
-
E.
Apalit
Apalit is a municipality in the province of Pampanga in the Philippines, known for its religious festivals and riverside communities along the Pampanga River.
- 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_69d6ada4cd388190ae3bbf83ff87057a |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94dfddf38819099263b8b1e804736 |
completed | April 10, 2026, 7:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f64bb5af708190b3786da334c3bf23 |
completed | May 2, 2026, 7:08 p.m. |
Created at: April 8, 2026, 9:57 p.m.