Triple
T18744902
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sulu |
E458383
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Siasi |
—
|
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: Siasi | Statement: [Sulu, hasMunicipality, Siasi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Siasi Context triple: [Sulu, hasMunicipality, Siasi]
-
A.
Siasi
chosen
Siasi is an island municipality in the southern Philippines known for its predominantly Muslim population, fishing-based economy, and location within the Sulu Sea.
-
B.
Siatista
Siatista is a historic town in Western Macedonia, Greece, known for its traditional mansions, fur trade, and cultural heritage.
-
C.
Saisiyat
The Saisiyat are one of Taiwan’s indigenous Austronesian-speaking peoples, known for their distinctive culture and the legendary Pasta’ay (Dwarf) ritual.
-
D.
Saihat
Saihat is a coastal city in Saudi Arabia’s Eastern Province, known for its fishing heritage and proximity to major oil and industrial centers in the Gulf region.
-
E.
Sikrai
Sikrai is a town located in the Dausa district of the Indian state of Rajasthan.
- 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_69d8d394dc308190b6725073f5db324c |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e57691c8688190b225cbd88493d9d1 |
completed | April 20, 2026, 12:42 a.m. |
Created at: April 10, 2026, 11:51 a.m.