Triple
T118058
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gallic rooster |
E2385
|
entity |
| Predicate | etymologyRelatedTo |
P453
|
FINISHED |
| Object | Latin word "gallus" |
—
|
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: Latin word "gallus" | Statement: [Gallic rooster, etymologyRelatedTo, Latin word "gallus"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: etymologyRelatedTo Context triple: [Gallic rooster, etymologyRelatedTo, Latin word "gallus"]
-
A.
etymologyType
Indicates the specific kind or category of etymological relationship that links a term to its linguistic origin or source.
-
B.
etymology
chosen
Indicates the historical origin and development of a word or term, including its source language and form.
-
C.
etymologicalLanguage
Indicates the language from which a word or term is historically derived in its etymology.
-
D.
relatedEthnicGroup
Indicates that there is a notable ethnic connection or association between two ethnic groups, such as shared ancestry, culture, or historical ties.
-
E.
hasCommonLoanwordsFrom
Indicates that two languages share loanwords that originate from the same source language.
- 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_69a2506c5428819085c28a8884790e29 |
completed | Feb. 28, 2026, 2:18 a.m. |
| NER | Named-entity recognition | batch_69a258e0b11c8190b7b5cf3c354c47ce |
completed | Feb. 28, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69a25646d5088190a057989c32da3a90 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:24 a.m.