Triple
T22098999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laguindingan Airport |
E546116
|
entity |
| Predicate | cityServed |
P82
|
FINISHED |
| Object | Gitagum |
—
|
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: Gitagum | Statement: [Laguindingan Airport, cityServed, Gitagum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gitagum Context triple: [Laguindingan Airport, cityServed, Gitagum]
-
A.
Gitagum
chosen
Gitagum is a coastal municipality in Misamis Oriental, Philippines, known for its scenic shoreline along Macajalar Bay and growing eco-tourism attractions.
-
B.
Giporlos
Giporlos is a coastal municipality in the province of Eastern Samar in the Philippines, known for its fishing communities and scenic seaside landscapes.
-
C.
Matagot
Matagot is a French board game publisher known for producing innovative and thematic tabletop games.
-
D.
Ganggalida
Ganggalida are an Aboriginal Australian people traditionally associated with the southern Gulf of Carpentaria region in Queensland.
-
E.
Gizo
Gizo is a small island town in the Solomon Islands known as an administrative and commercial hub in the western part of the country and a popular base for diving and marine tourism.
- 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_69e11e36d03c8190a83a1ba802b7231b |
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.