Triple
T32615427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Silvan Tomkins |
E833770
|
entity |
| Predicate | workContrastedWith |
P174935
|
FINISHED |
| Object | drive theory |
—
|
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: drive theory | Statement: [Silvan Tomkins, workContrastedWith, drive theory]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workContrastedWith Context triple: [Silvan Tomkins, workContrastedWith, drive theory]
-
A.
workFor
Indicates that one entity is employed by or performs work under the authority or direction of another entity.
-
B.
workRelatedTo
Indicates a relationship where one entity’s work, tasks, or professional activities are connected, associated, or relevant to those of another entity.
-
C.
workWith
Indicates that one entity collaborates or engages in work-related activities together with another entity.
-
D.
otherWork
Indicates that one work is related to another work by the same creator, but is distinct from the primary or referenced work.
-
E.
characterContrastWithWork
Indicates a relationship where a character’s traits, behavior, or role are intentionally contrasted with the themes, style, or overall nature of a work.
- 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_69f3492bfa648190b6ae472074634e29 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6c90790788190a1ed09adc86ed22d |
completed | May 3, 2026, 4:03 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f42fbc8190a06eb1044c9e6094 |
completed | May 3, 2026, 3:41 a.m. |
| PDg | Predicate description generation | batch_69f6c814c26c81908f5c47285129ff2a |
completed | May 3, 2026, 3:59 a.m. |
Created at: May 1, 2026, 1:06 a.m.