Triple
T7722214
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nahuatl |
E175038
|
entity |
| Predicate | loanwordsInEnglish |
P11431
|
FINISHED |
| Object | chocolate |
—
|
LITERAL 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: chocolate | Statement: [Nahuatl, loanwordsInEnglish, chocolate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: loanwordsInEnglish Context triple: [Nahuatl, loanwordsInEnglish, chocolate]
-
A.
loanwordsFrom
chosen
Indicates that one language has borrowed words from another language.
-
B.
hasCommonLoanwordsFrom
Indicates that two languages share loanwords that originate from the same source language.
-
C.
etymologicalLanguage
Indicates the language from which a word or term is historically derived in its etymology.
-
D.
languageInfluence
Indicates that one language has an effect on the development, usage, or characteristics of another language.
-
E.
lexicalResources
Indicates that one entity provides or is associated with lexical materials (such as dictionaries, vocabularies, or word lists) that support or describe another entity.
- F. None of above.
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_69c6995d541c81909eaa646b1a8369a9 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7074eca4c8190bd51fd1b450729e8 |
completed | March 27, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69c7016a6cf88190b53bf4b958f0f302 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:05 p.m.