Triple
T13413043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pilar, Bataan |
E320137
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Limay, Bataan |
E628679
|
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: Limay, Bataan | Statement: [Pilar, Bataan, locatedNear, Limay, Bataan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Limay, Bataan Context triple: [Pilar, Bataan, locatedNear, Limay, Bataan]
-
A.
Limay, Bataan
chosen
Limay, Bataan is a coastal industrial municipality in the province of Bataan in the Philippines, known for its petroleum refineries and power generation facilities.
-
B.
Pampanga River
The Pampanga River is a major river system in the Philippines that drains much of central Luzon, supporting extensive agriculture and communities along its floodplain.
-
C.
Marikina River
Marikina River is a major waterway in Metro Manila, Philippines, known for flowing through the city of Marikina and frequently causing floods in surrounding urban areas.
-
D.
Meycauayan River
Meycauayan River is a heavily polluted river in Bulacan, Philippines, known for flowing through industrial and residential areas before emptying into Manila Bay.
-
E.
Talisay River
Talisay River is a waterway located in the province of Bataan in the Philippines.
- 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_69d806b943cc8190b6af624d385d7e12 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaeb556948190af008c88e5bbf051 |
completed | April 12, 2026, 2:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7307e9b5881908eb2cd9e4fa7c5f2 |
completed | May 3, 2026, 11:24 a.m. |
Created at: April 9, 2026, 9:35 p.m.