Triple
T637394
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uto-Aztecan |
E16654
|
entity |
| Predicate | includesLanguage |
P2177
|
FINISHED |
| Object | Serrano |
E46489
|
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: Serrano | Statement: [Uto-Aztecan, includesLanguage, Serrano]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Serrano Context triple: [Uto-Aztecan, includesLanguage, Serrano]
-
A.
Serrano
chosen
Serrano are an Indigenous people of Southern California traditionally inhabiting the San Bernardino Mountains and surrounding desert regions.
-
B.
Spínola
Spínola is a Portuguese surname most prominently associated with António de Spínola, a key military figure and political leader during Portugal’s Carnation Revolution.
-
C.
Barra
Barra is a scenic island in the Outer Hebrides of Scotland, known for its rugged coastline, Gaelic culture, and the unique beach runway at Barra Airport.
-
D.
Barra
Barra is the surname of Mary Barra, the prominent American business executive and CEO of General Motors.
-
E.
Boyeros
Boyeros is a municipality in Havana, Cuba, known for hosting the country’s main international gateway, José Martí International Airport.
- 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_69a4936be1c88190af56540324b57da7 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49ee7fdbc8190858e42bb1bfdb3ff |
completed | March 1, 2026, 8:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a57405d6f48190b55542d50d3a1f22 |
completed | March 2, 2026, 11:27 a.m. |
Created at: March 1, 2026, 7:35 p.m.