Triple
T13942079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miss |
E335280
|
entity |
| Predicate | historicalDerivation |
P54889
|
FINISHED |
| Object | shortened from Mistress |
—
|
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: shortened from Mistress | Statement: [Miss, historicalDerivation, shortened from Mistress]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: historicalDerivation Context triple: [Miss, historicalDerivation, shortened from Mistress]
-
A.
historicalOrigin
Indicates the relationship by which one entity serves as the source, origin, or starting point in history for another entity.
-
B.
historicalOriginMeaning
chosen
Indicates that one entity explains the original historical source or derivational meaning of another entity.
-
C.
hasHistoricalOrigin
Indicates that something originated, was first established, or came into existence during a specific historical period or context.
-
D.
traditionalEtymology
Indicates that an entity’s origin or meaning is explained according to a historically established or customary etymological account.
-
E.
etymologyType
Indicates the specific kind or category of etymological relationship that links a term to its linguistic origin or source.
- 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_69d81c6081b88190b53e317c3370c8fe |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2cf6e29881908ddb8efca9a456a3 |
completed | April 14, 2026, 12:03 p.m. |
| PD | Predicate disambiguation | batch_69de05a3ccf88190b45c742db483fa08 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:17 p.m.