Triple
T22970360
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taylor |
E571169
|
entity |
| Predicate | etymologyNotes |
P58900
|
FINISHED |
| Object | from verbs meaning "to cut" or "to shape" cloth |
—
|
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: from verbs meaning "to cut" or "to shape" cloth | Statement: [Taylor, etymologyNotes, from verbs meaning "to cut" or "to shape" cloth]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: etymologyNotes Context triple: [Taylor, etymologyNotes, from verbs meaning "to cut" or "to shape" cloth]
-
A.
etymologicalNote
chosen
Indicates that there is a note explaining the origin, historical development, or source language of a term or name.
-
B.
etymologyContext
Indicates the contextual or situational background (such as time, place, culture, or domain) relevant to the origin and historical development of a word or term.
-
C.
etymology
Indicates the historical origin and development of a word or term, including its source language and form.
-
D.
etymologyType
Indicates the specific kind or category of etymological relationship that links a term to its linguistic origin or source.
-
E.
etymologyStatus
Indicates the status or reliability classification of an etymological explanation for a term or name.
- 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_69e245b2c6548190a0e4c7f2f7df2d48 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1823272c4819083e4653d231facec |
completed | April 29, 2026, 3:59 a.m. |
| PD | Predicate disambiguation | batch_69ef3b9101f48190a06c69dff26c6441 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:48 p.m.