Triple
T19331286
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quirino Province |
E483499
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Saguday |
—
|
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: Saguday | Statement: [Quirino Province, hasMunicipality, Saguday]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saguday Context triple: [Quirino Province, hasMunicipality, Saguday]
-
A.
Saguday
chosen
Saguday is a municipality in the landlocked province of Quirino in the Cagayan Valley region of the Philippines.
-
B.
Ludag
Ludag is a small coastal settlement on the island of South Uist in Scotland’s Outer Hebrides.
-
C.
Gudia
Gudia is an Indian film directed by acclaimed filmmaker Goutam Ghose, known for its sensitive storytelling and exploration of complex social and emotional themes.
-
D.
Savelugu
Savelugu is a town and district capital in northern Ghana known as an important local center for agriculture and trade.
-
E.
Sasad
Sasad is a primarily residential neighborhood in Budapest known for its green, hilly surroundings and relatively quiet, suburban character.
- 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_69d8e8d13e3c81909d91d1d5ec37c095 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e616422fa08190bf4bde4312ec7cf3 |
completed | April 20, 2026, 12:04 p.m. |
Created at: April 10, 2026, 1:33 p.m.