Triple
T9748420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cebu region |
E236374
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Naga City (Cebu) |
E445700
|
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: Naga City (Cebu) | Statement: [Cebu region, contains, Naga City (Cebu)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Naga City (Cebu) Context triple: [Cebu region, contains, Naga City (Cebu)]
-
A.
Naga City
chosen
Naga City is a component city in the province of Cebu in the Philippines, known for its industrial activities and coastal location in the central Visayas region.
-
B.
Naga City
Naga City is a major urban center in the Bicol Region of the Philippines, known as a cultural, religious, and educational hub.
-
C.
Cabanatuan City
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."
-
D.
Catbalogan
Catbalogan is a coastal city in the Philippines that serves as the capital and commercial hub of Samar province.
-
E.
Danao City
Danao City is a component city in the province of Cebu in the Philippines, known historically for its gun-making industry and as a growing commercial and industrial hub in the region.
- 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_69ca84d4eddc8190996fec1417d2bae8 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9f68f8b88190b44babf5ae17dfef |
completed | April 1, 2026, 10:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1b00d76488190af68cba694dc329c |
completed | April 5, 2026, 12:42 a.m. |
Created at: March 30, 2026, 8:23 p.m.