Triple
T9701430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Tapochau |
E234784
|
entity |
| Predicate | offersViewOf |
P3821
|
FINISHED |
| Object | Garapan |
E594785
|
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: Garapan | Statement: [Mount Tapochau, offersViewOf, Garapan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Garapan Context triple: [Mount Tapochau, offersViewOf, Garapan]
-
A.
Garapan
chosen
Garapan is the main commercial and tourist district of Saipan in the Northern Mariana Islands, known for its hotels, shops, and beachfront attractions.
-
B.
Balayan
Balayan is a historic coastal municipality in the province of Batangas in the Philippines, known for its heritage houses and annual Parada ng Lechon festival.
-
C.
Surigaonon
Surigaonon is a Visayan language spoken primarily in the Caraga region of northeastern Mindanao in the Philippines.
-
D.
Masbate
Masbate is an island province in the central Philippines, known for its cattle ranches, rodeo festivals, and location between Luzon and the Visayas.
-
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_69ca84cc78808190a56f3402b7c139a7 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9d70f55c8190934f37c25e9d4ba4 |
completed | April 1, 2026, 10:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1912e645881908d223a93f3ee61da |
completed | April 4, 2026, 10:31 p.m. |
Created at: March 30, 2026, 8:18 p.m.