Triple
T19448803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Utiroa |
E486556
|
entity |
| Predicate | hasNearbySettlement |
P4647
|
FINISHED |
| Object | Nuribenua |
—
|
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: Nuribenua | Statement: [Utiroa, hasNearbySettlement, Nuribenua]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nuribenua Context triple: [Utiroa, hasNearbySettlement, Nuribenua]
-
A.
Nuribenua
chosen
Nuribenua is a village settlement on the atoll of Tabiteuea in the island nation of Kiribati in the central Pacific Ocean.
-
B.
Kinoko Nasu
Kinoko Nasu is a Japanese writer and co-founder of Type-Moon, best known for creating influential visual novels and light novels such as Tsukihime, Fate/stay night, and The Garden of Sinners.
-
C.
Tite Kubo
Tite Kubo is a Japanese manga artist best known for creating the popular shonen series Bleach, which blends supernatural action with stylish character designs.
-
D.
Masuzu Natsukawa
Masuzu Natsukawa is the beautiful, silver-haired heroine of the romantic comedy light novel and anime series "Oreshura," known for her sharp tongue and manipulative yet vulnerable personality.
-
E.
Naoto Kubo
Naoto Kubo is a Japanese video game composer best known for his work on Nintendo titles, particularly in the Super Mario series.
- 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_69d8e8d7ad488190a3373045029b0f3b |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6338be5a48190973d9ecae853900c |
completed | April 20, 2026, 2:09 p.m. |
Created at: April 10, 2026, 1:38 p.m.