Triple
T36249103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Two Sisters |
E891745
|
entity |
| Predicate | creatorTrainedIn |
P22559
|
FINISHED |
| Object | classical academic tradition |
—
|
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: classical academic tradition | Statement: [The Two Sisters, creatorTrainedIn, classical academic tradition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: creatorTrainedIn Context triple: [The Two Sisters, creatorTrainedIn, classical academic tradition]
-
A.
creatorTrainedAt
Indicates that the creator of an entity received education or training at the specified institution or place.
-
B.
isTrainedBy
Indicates that one entity receives training, instruction, or coaching from another entity.
-
C.
trainedAs
chosen
Indicates that one entity has received education or instruction to perform the role, profession, or function represented by another entity.
-
D.
creatorType
Indicates the role or category of a creator in relation to the creation of something (e.g., author, artist, director).
-
E.
creatorOccupation
Indicates the professional role or job that the creator of an entity holds or held.
- 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_69f76e4599108190811532e707d6bc2c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ff97637ad881908c24fe2cc6b036db |
completed | May 9, 2026, 8:21 p.m. |
| PD | Predicate disambiguation | batch_69ff96c43a808190942eeda1934602db |
completed | May 9, 2026, 8:19 p.m. |
Created at: May 3, 2026, 4:09 p.m.