Triple
T11883922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Rough and Ready |
E282727
|
entity |
| Predicate | describesAppearanceOrManner |
P311
|
FINISHED |
| Object | rough |
—
|
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: rough | Statement: [Old Rough and Ready, describesAppearanceOrManner, rough]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: describesAppearanceOrManner Context triple: [Old Rough and Ready, describesAppearanceOrManner, rough]
-
A.
styleDescribedAs
Indicates that the manner, aesthetic, or mode of something is characterized or labeled using a particular style description.
-
B.
appearance
chosen
Indicates how something looks or seems to an observer, including its visible form, condition, or outward impression.
-
C.
hasCharacterAppearance
Indicates that a character appears or is visually represented within a given work, scene, or context.
-
D.
fashionCharacteristic
Indicates a relationship where one entity possesses or exhibits a particular style, trend, or fashion-related attribute in relation to another.
-
E.
styleTendsTo
Indicates that one style is generally inclined or likely to develop, appear, or be adopted in the direction of another style.
- 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_69d6ab2a90b08190a4e818821cc93e6d |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8d3a02ad4819090faef0e0be732ee |
completed | April 10, 2026, 10:40 a.m. |
| PD | Predicate disambiguation | batch_69d8bb272f88819090c37c944c5a60ab |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:44 p.m.