Triple
T22099095
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Capitol University |
E546119
|
entity |
| Predicate | city |
P40
|
FINISHED |
| Object | Cagayan de Oro |
—
|
NE NERFINISHED |
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: Cagayan de Oro | Statement: [Capitol University, city, Cagayan de Oro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cagayan de Oro Context triple: [Capitol University, city, Cagayan de Oro]
-
A.
Cagayan de Oro
chosen
Cagayan de Oro is a highly urbanized city in Northern Mindanao, Philippines, known as a regional economic hub and gateway to the island’s northern corridor.
-
B.
Davao City
Davao City is a major urban center in the southern Philippines known for its economic hub status, proximity to Mount Apo, and reputation as one of the country’s safest and most progressive cities.
-
C.
Cotabato City
Cotabato City is an independent urban center in the southern Philippines known as a key political, economic, and cultural hub in Mindanao.
-
D.
Iloilo City
Iloilo City is a highly urbanized coastal city in the central Philippines known as a commercial, educational, and cultural hub of the Western Visayas region.
-
E.
バギオ
バギオは、フィリピン北部ルソン島の山岳地帯に位置し、冷涼な気候と避暑地としての人気から「夏の首都」とも呼ばれる都市である。
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e378dc08190896d6a51597afd5a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f129131b4c8190b443bc820d9b5c61 |
completed | April 28, 2026, 9:39 p.m. |
Created at: April 16, 2026, 8:30 p.m.