Triple
T8058292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | turn (Kehre) in Heidegger’s philosophy |
E188053
|
entity |
| Predicate | fromFocusOn |
P31
|
FINISHED |
| Object | analytic of Dasein |
—
|
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: analytic of Dasein | Statement: [turn (Kehre) in Heidegger’s philosophy, fromFocusOn, analytic of Dasein]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fromFocusOn Context triple: [turn (Kehre) in Heidegger’s philosophy, fromFocusOn, analytic of Dasein]
-
A.
focusesOn
chosen
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
B.
lessFocusOn
Indicates that one entity directs reduced attention, emphasis, or priority toward another entity or activity compared to alternatives.
-
C.
canonicalFocus
Indicates that one entity is the primary or most representative focus or point of attention in relation to another entity.
-
D.
focusesBy
Indicates that one entity directs its attention, effort, or emphasis toward another entity or specific aspect of it.
-
E.
formerFocus
Indicates that an entity previously served as the primary focus or main subject of attention, but no longer holds that status.
- 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_69ca82b2f68881908c50560697e210da |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3fa51adc8190b9327441bd8b9fb3 |
completed | March 31, 2026, 3:29 a.m. |
| PD | Predicate disambiguation | batch_69cb049a1b9c8190811c396421ebf9c9 |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:25 p.m.