Triple
T22626881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | He Sapa |
E558443
|
entity |
| Predicate | hasAlternativeTransliteration |
P5923
|
FINISHED |
| Object | Ȟe Sapa |
—
|
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: Ȟe Sapa | Statement: [He Sapa, hasAlternativeTransliteration, Ȟe Sapa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ȟe Sapa Context triple: [He Sapa, hasAlternativeTransliteration, Ȟe Sapa]
-
A.
He Sapa
chosen
He Sapa is the Lakota name for the Black Hills, a region in present-day South Dakota and Wyoming that holds profound spiritual and cultural significance for the Lakota and other Indigenous peoples.
-
B.
Huaytará
Huaytará is a town in the Huancavelica Region of Peru known as an administrative and commercial center in the Andean highlands.
-
C.
Sangolquí
Sangolquí is a city in central Ecuador known as a growing suburban and commercial center near the capital, Quito, within Pichincha Province.
-
D.
Ojochal
Ojochal is a small coastal village in southern Costa Rica known for its tranquil beaches, lush rainforest surroundings, and notable international dining scene.
-
E.
Pasuquin
Pasuquin is a coastal municipality in the province of Ilocos Norte in the Philippines, known for its salt-making industry and scenic beaches.
- 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_69e245467d9881908d6985bd0db7a1f1 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f16e3e09ec8190af940c25c7e8e029 |
completed | April 29, 2026, 2:34 a.m. |
Created at: April 17, 2026, 3:01 p.m.