Triple
T37931389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lectures on the English Poets |
E946226
|
entity |
| Predicate | coversPoet |
P141336
|
FINISHED |
| Object | Geoffrey Chaucer |
—
|
NE NERFINISHED |
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: Geoffrey Chaucer | Statement: [Lectures on the English Poets, coversPoet, Geoffrey Chaucer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coversPoet Context triple: [Lectures on the English Poets, coversPoet, Geoffrey Chaucer]
-
A.
featuredPoet
Indicates that a person is highlighted or showcased as a poet in a special or prominent context.
-
B.
favoritePoet
Indicates that one entity is the poet whom another entity prefers above all other poets.
-
C.
poet
Indicates that an entity creates poetry or is recognized for engaging in the activity of writing poems.
-
D.
containsPoemsFrom
chosen
Indicates that one entity includes or features poems that originate from or are authored in association with another entity.
-
E.
coverComposer
Indicates that one entity is the composer of the music for another entity that is a cover version of a work.
- 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_69f76ef3b7248190892fb9706423be7c |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fd6a1c1c4881908090053bc359b181 |
completed | May 8, 2026, 4:44 a.m. |
| PD | Predicate disambiguation | batch_69fd696f24d8819091033afacbdaadc5 |
completed | May 8, 2026, 4:41 a.m. |
Created at: May 3, 2026, 4:20 p.m.