Triple
T22748311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maya Port |
E562615
|
entity |
| Predicate | distanceFrom |
P1299
|
FINISHED |
| Object | Cebu City |
—
|
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: Cebu City | Statement: [Maya Port, distanceFrom, Cebu City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cebu City Context triple: [Maya Port, distanceFrom, Cebu City]
-
A.
Cebu
chosen
Cebu is a major island and province in the central Philippines known for its historic role in Spanish colonization, vibrant urban center Cebu City, and popular beach and dive tourism.
-
B.
Cagayan de Oro
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.
-
C.
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.
-
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_69e245513a5c81908d5cb471b4fc429d |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f179b702388190b134dde5f80ea3cd |
completed | April 29, 2026, 3:23 a.m. |
Created at: April 17, 2026, 3:24 p.m.