Triple
T581831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kumeyaay language |
E15074
|
entity |
| Predicate | hasDialect |
P4251
|
FINISHED |
| Object | Ipai |
E75124
|
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: Ipai | Statement: [Kumeyaay language, hasDialect, Ipai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ipai Context triple: [Kumeyaay language, hasDialect, Ipai]
-
A.
Ipai-Tipai
chosen
Ipai-Tipai is a Yuman language of the Kumeyaay people indigenous to the Baja California and southern California region.
-
B.
Lapa
Lapa is a historic and bohemian neighborhood in Rio de Janeiro, Brazil, famous for its vibrant nightlife, samba clubs, and iconic aqueduct arches.
-
C.
Madura
Madura is an island off the northeastern coast of Java in Indonesia, known for its distinct Madurese culture and traditional bull races.
-
D.
Fiambalá
Fiambalá is a small town in northwestern Argentina known for its high-altitude vineyards, desert landscapes, and nearby Andean mountain passes.
-
E.
Lipara
Lipara is one of the Hesperides, the nymphs of Greek mythology associated with the evening and the golden apples of the gods.
- 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_69a4935783b8819082b77726ec10cc42 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49b84899881909d5b2b4e67e22d9b |
completed | March 1, 2026, 8:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a5914232c481909a39cd3373e3c6c9 |
completed | March 2, 2026, 1:31 p.m. |
Created at: March 1, 2026, 7:33 p.m.