Triple
T11905256
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Union |
E283255
|
entity |
| Predicate | hasCoastalTown |
P969
|
FINISHED |
| Object | Agoo |
E562605
|
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: Agoo | Statement: [La Union, hasCoastalTown, Agoo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Agoo Context triple: [La Union, hasCoastalTown, Agoo]
-
A.
Agoo
chosen
Agoo is a coastal municipality in the province of La Union, Philippines, known for its fishing communities, beaches, and historical churches along the Lingayen Gulf.
-
B.
Gooigi
Gooigi is a green, goo-like doppelgänger of Luigi from the Luigi’s Mansion series, used as a playable helper character to solve puzzles and reach otherwise inaccessible areas.
-
C.
Aokas
Aokas is a coastal town in northern Algeria known for its Mediterranean beaches, karst caves, and location along the scenic shoreline of Béjaïa Province.
-
D.
Aahoo
Aahoo is the Persian birth name of American actress and former NFL cheerleader Sarah Shahi.
-
E.
Aozou
Aozou is a small, remote settlement in northern Chad, historically associated with the disputed Aozou Strip along the Chadian–Libyan border.
- 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_69d6ab2c07e88190ba13b0d21fd6cf33 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8e525460c81909d855048d9c799bf |
completed | April 10, 2026, 11:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f44004b454819091b41bac99895106 |
completed | May 1, 2026, 5:54 a.m. |
Created at: April 8, 2026, 9:44 p.m.