Triple
T27030864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nomes |
E680912
|
entity |
| Predicate | commonAdversary |
P178583
|
FINISHED |
| Object | Ozma |
—
|
NE NERFINISHED |
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: Ozma | Statement: [Nomes, commonAdversary, Ozma]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonAdversary Context triple: [Nomes, commonAdversary, Ozma]
-
A.
otherAdversary
Indicates that one entity is an adversary of another, distinct from any primary or previously identified adversary.
-
B.
primaryAdversaryImplied
Indicates that an entity is understood or suggested, rather than explicitly stated, to be the main opponent or chief adversary of another entity.
-
C.
primaryAdversaryContext
Indicates the main opposing force or conflict-driving element that defines the central adversarial situation within a given context.
-
D.
notableAdversary
Indicates that one entity is recognized as a significant or prominent opponent or rival of another entity.
-
E.
modelsAdversary
Indicates that one entity represents, simulates, or formally characterizes another entity as an adversary within a given context or system.
- 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_69eeeb5566f08190813daf896fa3da04 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f7117e55908190a67105e92bc4830f |
completed | May 3, 2026, 9:12 a.m. |
| PD | Predicate disambiguation | batch_69f70f380690819090cc34763ba460ed |
completed | May 3, 2026, 9:02 a.m. |
| PDg | Predicate description generation | batch_69f7117cf2188190b29e36fc1e342c60 |
completed | May 3, 2026, 9:12 a.m. |
Created at: April 27, 2026, 7:13 a.m.