Triple
T29185794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stephen Byerley |
E739864
|
entity |
| Predicate | controversyInStory |
P190666
|
FINISHED |
| Object | accusations of being a robot |
—
|
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: accusations of being a robot | Statement: [Stephen Byerley, controversyInStory, accusations of being a robot]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: controversyInStory Context triple: [Stephen Byerley, controversyInStory, accusations of being a robot]
-
A.
controversy
Indicates a situation in which there is active disagreement, dispute, or public debate between parties over a particular issue, action, or claim.
-
B.
controversialBecause
Indicates that one entity is considered controversial specifically due to, or as a result of, its relationship with or association to another entity.
-
C.
controversyType
Indicates the specific kind or category of controversy associated with an entity or situation.
-
D.
locationOfControversy
Indicates the place or setting where a dispute, debate, or controversy occurs or is centered.
-
E.
dataControversy
Indicates that there is dispute, concern, or disagreement surrounding the collection, use, interpretation, or ownership of certain data.
- 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_69f07cb74c2c8190ad396487fcb4fde6 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69fcce2cf9188190b3f65b362203a6a3 |
completed | May 7, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69fcccee6240819084680887731ff64b |
completed | May 7, 2026, 5:33 p.m. |
| PDg | Predicate description generation | batch_69fccdd2d84481909a7ce22407def9c7 |
completed | May 7, 2026, 5:37 p.m. |
Created at: April 28, 2026, 11:59 a.m.