Triple
T9483592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kawasan Falls |
E228706
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Badian |
E261532
|
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: Badian | Statement: [Kawasan Falls, locatedIn, Badian]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Badian Context triple: [Kawasan Falls, locatedIn, Badian]
-
A.
Badian
chosen
Badian is a coastal municipality in southwestern Cebu, Philippines, known for attractions like Kawasan Falls and canyoneering activities.
-
B.
Bahdini
Bahdini is a Northern Kurdish dialect spoken primarily in parts of Turkey and Iraq.
-
C.
Bagoas
Bagoas is a historical figure known primarily from ancient sources, though details about this individual—beyond being linked genealogically to the Numidian king Masinissa—are sparse and uncertain.
-
D.
Bariadi
Bariadi is a town in northern Tanzania that serves as an important local administrative and commercial center.
-
E.
Busaiteen
Busaiteen is a coastal town in the Kingdom of Bahrain, located on Muharraq Island and known for its residential neighborhoods and proximity to Bahrain International Airport.
- 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_69ca84730a5081908de282651019bf2f |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd804c859081908c261ad16b501f0d |
completed | April 1, 2026, 8:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d12d0bf0c08190ab96db3eb522c91e |
completed | April 4, 2026, 3:23 p.m. |
Created at: March 30, 2026, 7:55 p.m.