Triple
T1866553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Autocrat |
E34933
|
entity |
| Predicate | characterFunction |
P33244
|
FINISHED |
| Object | vehicle for author’s opinions |
—
|
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: vehicle for author’s opinions | Statement: [The Autocrat, characterFunction, vehicle for author’s opinions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterFunction Context triple: [The Autocrat, characterFunction, vehicle for author’s opinions]
-
A.
character2
Indicates that a second character entity is involved in the relationship or context defined by the predicate.
-
B.
characterizedBy
Indicates that one entity possesses a defining quality, feature, or attribute expressed by another entity.
-
C.
character1
Indicates that the subject is identified as the first or primary character in a narrative or context.
-
D.
containsCharacter
Indicates that one entity includes a specific character as part of its content or composition.
-
E.
regionCharacter
Indicates a characteristic, feature, or quality that typifies or defines a particular region.
- 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_69a88600b2f88190bc09303e68ab517e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abb16c09e48190a345c95eab59fd87 |
completed | March 7, 2026, 5:02 a.m. |
| PD | Predicate disambiguation | batch_69abafe02c3c819093a4744b476106ca |
completed | March 7, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69abb16a6db48190af04012e8ed2269f |
completed | March 7, 2026, 5:02 a.m. |
Created at: March 4, 2026, 7:34 p.m.