Triple
T16217663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metro Cebu |
E393634
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Liloan |
E261534
|
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: Liloan | Statement: [Metro Cebu, hasMunicipality, Liloan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Liloan Context triple: [Metro Cebu, hasMunicipality, Liloan]
-
A.
Liloan
chosen
Liloan is a coastal municipality in the province of Cebu in the Philippines, known for its historic lighthouse and scenic shoreline.
-
B.
Liloan
Liloan is a coastal municipality in the province of Southern Leyte in the Philippines, known for its fishing communities and scenic seaside landscapes.
-
C.
Pajo
Pajo is a barangay (village-level administrative division) located in the municipality of Daanbantayan in Cebu, Philippines.
-
D.
Nanakuli
Nanakuli is a coastal community on the leeward side of Oahu in Hawaii, known for its beaches and strong Native Hawaiian presence.
-
E.
Lawaan
Lawaan is a coastal municipality in the province of Eastern Samar in the Philippines, known for its rural communities and natural landscapes.
- 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_69d87f1f5bd08190bd01cac0d5b9d2ef |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e227f76f748190831d230d32c18611 |
completed | April 17, 2026, 12:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0017ab10a48190afa19e74c0059427 |
completed | May 10, 2026, 5:29 a.m. |
Created at: April 10, 2026, 5:03 a.m.