Triple
T16191359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Danny Maccabee |
E392947
|
entity |
| Predicate | usesDeception |
P22080
|
FINISHED |
| Object | pretends to be married |
—
|
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: pretends to be married | Statement: [Danny Maccabee, usesDeception, pretends to be married]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesDeception Context triple: [Danny Maccabee, usesDeception, pretends to be married]
-
A.
typeOfDeception
Indicates the specific kind or category of deceptive act that one entity employs toward another or in a given context.
-
B.
threatensDeceptionOf
Indicates that one entity poses or communicates a risk of deceiving or misleading another entity.
-
C.
disguisedAs
Indicates that one entity is intentionally presenting itself as, or made to appear as, another entity in order to conceal its true identity.
-
D.
decoyType
Indicates that one entity functions as a decoy and specifies the type or category of that decoy in relation to another entity or context.
-
E.
usesMasksOrDisguises
chosen
Indicates that an entity employs masks, costumes, or other forms of disguise to conceal or alter its identity in the context of an action or interaction.
- 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_69d87f1e49ac8190a311b54d32990576 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e222d5769c8190bbb604bfa095a1a5 |
completed | April 17, 2026, 12:08 p.m. |
| PD | Predicate disambiguation | batch_69e219e11f6081909106b1240a17fd37 |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:02 a.m.