Triple
T8054587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Persia and the Persian Question |
E187764
|
entity |
| Predicate | hasBias |
P47259
|
FINISHED |
| Object | pro-British imperial |
—
|
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: pro-British imperial | Statement: [Persia and the Persian Question, hasBias, pro-British imperial]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBias Context triple: [Persia and the Persian Question, hasBias, pro-British imperial]
-
A.
bias
chosen
Indicates a systematic preference or prejudice in favor of or against an entity, affecting how it is treated, evaluated, or represented relative to others.
-
B.
hasNotablePositionBias
Indicates that an entity systematically favors or disfavors certain positions or placements over others in a notable or measurable way.
-
C.
hasMean
Indicates that one entity possesses, exhibits, or is characterized by a particular mean value or average.
-
D.
isHeavilyWeightedToward
Indicates that something is strongly biased or disproportionately oriented in favor of one side, option, or aspect over others.
-
E.
hasTendency
Indicates that an entity is inclined or likely to exhibit a particular behavior, characteristic, or outcome under certain conditions.
- 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_69ca82b15e948190a62fd7af5218426a |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3f9fb8dc8190bacc1f66ddfd1cbf |
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.