Triple
T524211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cook |
E10881
|
entity |
| Predicate | etymologicalType |
P2530
|
FINISHED |
| Object | occupational name |
—
|
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: occupational name | Statement: [Cook, etymologicalType, occupational name]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: etymologicalType Context triple: [Cook, etymologicalType, occupational name]
-
A.
etymologyType
chosen
Indicates the specific kind or category of etymological relationship that links a term to its linguistic origin or source.
-
B.
etymologicalSource
Indicates that one term or name originates from, is derived from, or has its roots in another term or name.
-
C.
etymologicalLanguage
Indicates the language from which a word or term is historically derived in its etymology.
-
D.
etymologicalForm
Indicates that one linguistic form is derived from, or historically originates in, another form as its etymological source.
-
E.
etymology
Indicates the historical origin and development of a word or term, including its source language and form.
- 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_69a2e84b16c4819088d284c47c3a7968 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f1b656c08190b387f21b06d99e68 |
completed | Feb. 28, 2026, 1:46 p.m. |
| PD | Predicate disambiguation | batch_69a2f018129c81909494450fcba71b59 |
completed | Feb. 28, 2026, 1:39 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.