Triple
T8448559
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cabanatuan POW camp |
E199742
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Cabanatuan |
E473591
|
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: Cabanatuan | Statement: [Cabanatuan POW camp, locatedIn, Cabanatuan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cabanatuan Context triple: [Cabanatuan POW camp, locatedIn, Cabanatuan]
-
A.
Cabanatuan City
chosen
Cabanatuan City is a highly urbanized commercial and transportation hub in the Philippine province of Nueva Ecija, historically known as the "Tricycle Capital of the Philippines."
-
B.
Dipaculao
Dipaculao is a coastal municipality in the Philippine province of Aurora known for its beaches, surfing spots, and scenic mountain landscapes.
-
C.
Tarlac
Tarlac is a landlocked province in the Central Luzon region of the Philippines known for its culturally diverse population and agricultural economy.
-
D.
Baliuag
Baliuag is a first-class municipality in the province of Bulacan in the Philippines, known as a commercial and educational hub in Central Luzon.
-
E.
Sagay
Sagay is a coastal municipality on Camiguin Island in the Philippines known for its rural communities and access to beaches and marine resources.
- 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_69ca83170f9081909cd98f55614c6476 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe445b7988190b53ae45070c70d1d |
completed | March 31, 2026, 3:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cecc3c0d508190bc0c7bd89f040967 |
completed | April 2, 2026, 8:06 p.m. |
Created at: March 30, 2026, 6:09 p.m.