Triple
T15983985
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Macabebe |
E387644
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Masantol |
E398573
|
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: Masantol | Statement: [Macabebe, borderedBy, Masantol]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Masantol Context triple: [Macabebe, borderedBy, Masantol]
-
A.
Masantol
chosen
Masantol is a coastal municipality in the province of Pampanga in the Philippines, known for its fishing communities and riverine landscapes along the Pampanga River delta.
-
B.
Bansalan
Bansalan is a municipality in the province of Davao del Sur in the Philippines, known for its agricultural economy and rural communities.
-
C.
Abucay
Abucay is a coastal municipality in the province of Bataan in the Philippines, known for its historical significance dating back to the Spanish colonial period.
-
D.
Meycauayan
Meycauayan is a highly urbanized city in the Philippine province of Bulacan known for its jewelry and leather industries.
-
E.
Tagaytay
Tagaytay is a popular highland city in the Philippines known for its cool climate and scenic views of Taal Volcano and Taal Lake.
- 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e15756d6488190ac35da00e96ce21d |
completed | April 16, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffc3cdf7848190848e9081027dc027 |
completed | May 9, 2026, 11:31 p.m. |
Created at: April 10, 2026, 4:54 a.m.