Triple
T19403563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M-i-k-e H-u-n-t |
E485389
|
entity |
| Predicate | appropriateness |
P97883
|
FINISHED |
| Object | not suitable for formal contexts |
—
|
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: not suitable for formal contexts | Statement: [M-i-k-e H-u-n-t, appropriateness, not suitable for formal contexts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appropriateness Context triple: [M-i-k-e H-u-n-t, appropriateness, not suitable for formal contexts]
-
A.
lessSuitableFor
Indicates that one entity is comparatively less appropriate, effective, or fitting than another for a given purpose, context, or condition.
-
B.
allows
Indicates that one entity grants permission, capability, or opportunity for another entity to perform an action or be in a certain state.
-
C.
decorum
chosen
Indicates adherence to socially accepted standards of proper, polite, or appropriate behavior in a given context.
-
D.
suit
Indicates that one entity is appropriate, fitting, or satisfactory for another entity or a particular purpose or situation.
-
E.
aspect
Indicates a specific temporal phase or manner in which an action, event, or state unfolds or is viewed (e.g., ongoing, completed, habitual).
- 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_69d8e8d5162481909db12435d9535c1a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6257937d081909dbc5804d2505938 |
completed | April 20, 2026, 1:09 p.m. |
| PD | Predicate disambiguation | batch_69e4fd68b1f881908d273de1fee81a75 |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:36 p.m.