Triple
T14476980
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ohio Impromptu |
E358997
|
entity |
| Predicate | hasMinimalism |
P46648
|
FINISHED |
| Object | sparse dialogue |
—
|
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: sparse dialogue | Statement: [Ohio Impromptu, hasMinimalism, sparse dialogue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMinimalism Context triple: [Ohio Impromptu, hasMinimalism, sparse dialogue]
-
A.
hasMinimalistProduction
chosen
Indicates that something is produced or arranged using a sparse, simple, and stripped-down style with minimal elements or embellishment.
-
B.
hasMinimalInterface
Indicates that one entity provides only the smallest necessary set of methods, features, or interaction points required for another entity to use or interact with it.
-
C.
hasMiniature
Indicates that one entity possesses or includes a smaller-scale representation or model of another entity.
-
D.
minimizedBy
Indicates that one entity serves to reduce, lessen, or make as small as possible the value, effect, or impact of another entity.
-
E.
hasMinbar
Indicates that a location or structure contains or is equipped with a minbar (a pulpit used for sermons in a mosque).
- 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_69d827966698819082e140837737501d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de9248edb48190a74eb032aeaac027 |
completed | April 14, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69de5c42bd3c81909a62acf30cc24d1e |
completed | April 14, 2026, 3:24 p.m. |
Created at: April 10, 2026, 1:20 a.m.