Triple
T21445518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mrs. Fisher |
E529061
|
entity |
| Predicate | settingOfTransformation |
P144374
|
FINISHED |
| Object | Italian holiday |
—
|
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: Italian holiday | Statement: [Mrs. Fisher, settingOfTransformation, Italian holiday]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingOfTransformation Context triple: [Mrs. Fisher, settingOfTransformation, Italian holiday]
-
A.
setting
Indicates the place, time, or context in which an event, action, or interaction occurs.
-
B.
usesTransformation
Indicates that one entity applies or relies on a specific transformation process, method, or function to operate on or convert another entity.
-
C.
settingAfter
Indicates that one setting or configuration occurs or is applied after another in a sequence or order.
-
D.
settingOfRule
Indicates the contextual environment, domain, or circumstances within which a particular rule is defined and intended to apply.
-
E.
transformationProperty
Indicates that one entity has a specific behavior, constraint, or characteristic related to how it changes, converts, or is transformed into another form or state.
- F. None of above. chosen
Provenance (4 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_69e0c457579481909db68053ed99750c |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e8b707ecd88190b3576b8923840870 |
completed | April 22, 2026, 11:54 a.m. |
| PD | Predicate disambiguation | batch_69e631df1b38819088d3604854e697b4 |
completed | April 20, 2026, 2:02 p.m. |
| PDg | Predicate description generation | batch_69e63d2aca38819094d312078feaa436 |
completed | April 20, 2026, 2:50 p.m. |
Created at: April 16, 2026, 6:05 p.m.