Triple
T20512779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yao’s next-bit test |
E503604
|
entity |
| Predicate | adversaryView |
P140383
|
FINISHED |
| Object | adversary sees prefix of the sequence |
—
|
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: adversary sees prefix of the sequence | Statement: [Yao’s next-bit test, adversaryView, adversary sees prefix of the sequence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adversaryView Context triple: [Yao’s next-bit test, adversaryView, adversary sees prefix of the sequence]
-
A.
otherAdversary
Indicates that one entity is an adversary of another, distinct from any primary or previously identified adversary.
-
B.
modelsAdversary
Indicates that one entity represents, simulates, or formally characterizes another entity as an adversary within a given context or system.
-
C.
portraysAdversary
Indicates that one entity depicts or represents another entity as an opponent, enemy, or rival.
-
D.
primaryAdversaryContext
Indicates the main opposing force or conflict-driving element that defines the central adversarial situation within a given context.
-
E.
primaryAdversaryDirection
Indicates the direction from an entity toward its main or most significant adversary.
- 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_69e0b4b2aa788190ae9eb37c1d73b1f1 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69dcd74c48190b050e25c20154c09 |
completed | April 20, 2026, 9:42 p.m. |
| PD | Predicate disambiguation | batch_69e59fdb7ad88190924176c32a195db3 |
completed | April 20, 2026, 3:39 a.m. |
| PDg | Predicate description generation | batch_69e5a6a824748190bbe6192d73f3c613 |
completed | April 20, 2026, 4:08 a.m. |
Created at: April 16, 2026, 11:36 a.m.