Triple
T20426707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suzanne Beckett |
E501019
|
entity |
| Predicate | roleInSamuelBeckettLife |
P140092
|
FINISHED |
| Object | personal support |
—
|
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: personal support | Statement: [Suzanne Beckett, roleInSamuelBeckettLife, personal support]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInSamuelBeckettLife Context triple: [Suzanne Beckett, roleInSamuelBeckettLife, personal support]
-
A.
literaryRole
Indicates the specific narrative or functional role an entity holds within a literary work or text.
-
B.
roleInKeatsLife
Indicates the specific role or relationship an entity had in the life of Keats.
-
C.
roleInKierkegaardAuthorship
Indicates the specific role or contribution an entity has in the authorship or creation of works associated with Kierkegaard.
-
D.
notableWorkRole
Indicates that a person’s role or position is specifically associated with the creation, performance, or contribution to a notable work.
-
E.
authorOfWorkHeAppearsIn
Indicates that a person is the author of a work in which he himself appears as a character or subject.
- 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_69e0b4aa68fc8190b1a14c55575ef04a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67ba9700481909fa23493f98095d1 |
completed | April 20, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_69e5766df0008190a73c4f613c29678f |
completed | April 20, 2026, 12:42 a.m. |
| PDg | Predicate description generation | batch_69e58d766b408190a1d3698145fb6d30 |
completed | April 20, 2026, 2:20 a.m. |
Created at: April 16, 2026, 11:30 a.m.