Triple
T35512382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Princess |
E1026317
|
entity |
| Predicate | etymologyVia |
P5801
|
FINISHED |
| Object | Old French princesse |
—
|
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: Old French princesse | Statement: [Princess, etymologyVia, Old French princesse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: etymologyVia Context triple: [Princess, etymologyVia, Old French princesse]
-
A.
etymologyStatus
Indicates the status or reliability classification of an etymological explanation for a term or name.
-
B.
etymologicalSource
chosen
Indicates that one term or name originates from, is derived from, or has its roots in another term or name.
-
C.
etymologyType
Indicates the specific kind or category of etymological relationship that links a term to its linguistic origin or source.
-
D.
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.
-
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_69f76dfd61208190b93ec6dc439cab41 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79ec355048190af30123ceb6efa2b |
completed | May 3, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69f79e4bdbcc8190be7a0d2cf8a77b64 |
completed | May 3, 2026, 7:13 p.m. |
Created at: May 3, 2026, 4:04 p.m.