Triple
T9896460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Constantin Constantius |
E182185
|
entity |
| Predicate | hasAuthorialFunction |
P39728
|
FINISHED |
| Object | to distance Kierkegaard from the text |
—
|
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: to distance Kierkegaard from the text | Statement: [Constantin Constantius, hasAuthorialFunction, to distance Kierkegaard from the text]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAuthorialFunction Context triple: [Constantin Constantius, hasAuthorialFunction, to distance Kierkegaard from the text]
-
A.
hasFictionalFunction
Indicates that an entity serves a role, purpose, or function within a fictional context or narrative.
-
B.
hasAuthorialStance
chosen
Indicates that an entity expresses, embodies, or is associated with a particular author’s viewpoint, attitude, or perspective toward its subject matter.
-
C.
hasAuthor
Indicates that an entity is written or created by a specific author.
-
D.
hasAuthorCharacteristic
Indicates that an author possesses a particular attribute, trait, or quality.
-
E.
hasPrimaryFunction
Indicates that one entity serves as the main or principal function or role of another entity.
- 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_69ca82876f8081909cf75df0f99bb13f |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cdb4a9d2f4819086cfdd42b613cd8c |
completed | April 2, 2026, 12:13 a.m. |
| PD | Predicate disambiguation | batch_69cd1d872d50819096b7ab166a8decf1 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:40 p.m.