Triple
T22168085
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arekuna |
E547847
|
entity |
| Predicate | culturallyRelatedTo |
P22474
|
FINISHED |
| Object | Akawaio |
—
|
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: Akawaio | Statement: [Arekuna, culturallyRelatedTo, Akawaio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Akawaio Context triple: [Arekuna, culturallyRelatedTo, Akawaio]
-
A.
Akawaio
chosen
The Akawaio are an Indigenous people of the Guiana Highlands in Guyana, Venezuela, and Brazil, known for their Cariban language and traditional forest-based way of life.
-
B.
Kumaiwa
Kumaiwa is a small settlement located on Butaritari Atoll in the island nation of Kiribati in the central Pacific Ocean.
-
C.
Asago
Asago is a city in northern Hyōgo Prefecture, Japan, known for its mountainous scenery, historic castle ruins, and hot spring resorts.
-
D.
Kawazu
Kawazu is a small coastal town in Shizuoka Prefecture, Japan, known for its early-blooming Kawazu-zakura cherry blossoms and hot spring resorts.
-
E.
Nakawa
Nakawa is one of the energetic human hosts in Disney’s “Festival of the Lion King” stage show at Disney’s Animal Kingdom.
- 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_69e11e3c4c5c81908d336165816b12e0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12a6642b08190980fa0c0d2bb4229 |
completed | April 28, 2026, 9:45 p.m. |
Created at: April 16, 2026, 8:34 p.m.