Triple
T36406146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arabic root R-Š-D (رشَد) |
E896753
|
entity |
| Predicate | contrastsWithMeaning |
P123206
|
FINISHED |
| Object | misguidance |
—
|
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: misguidance | Statement: [Arabic root R-Š-D (رشَد), contrastsWithMeaning, misguidance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: contrastsWithMeaning Context triple: [Arabic root R-Š-D (رشَد), contrastsWithMeaning, misguidance]
-
A.
oftenContrastedWith
Indicates that one entity is frequently compared to another in a way that highlights their differences or opposing characteristics.
-
B.
providesContrastWith
chosen
Indicates that one entity is used to highlight differences or distinctions when compared with another entity.
-
C.
exploresContrastBetween
Indicates a relationship in which one entity examines, highlights, or analyzes the differences or oppositions between two or more entities, ideas, or situations.
-
D.
dramaticContrastWith
Indicates that one entity is presented in a way that sharply emphasizes differences in tone, style, or impact when compared with another entity.
-
E.
contrastUse
Indicates that one entity is used in opposition or distinction to another to highlight differences between them.
- 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_69f76e53b81081908d3b81860593f38a |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ff16775a9881909d26dbc1f0ef3e1c |
completed | May 9, 2026, 11:11 a.m. |
| PD | Predicate disambiguation | batch_69ff158e61708190a1c581d0d306cfce |
completed | May 9, 2026, 11:07 a.m. |
Created at: May 3, 2026, 4:10 p.m.