Triple
T33639672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Collard Greens |
E861796
|
entity |
| Predicate | containsMultilingualWordplay |
P201948
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Collard Greens, containsMultilingualWordplay, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsMultilingualWordplay Context triple: [Collard Greens, containsMultilingualWordplay, yes]
-
A.
isPlayOnWordsWith
Indicates a relationship where one expression is a pun or wordplay that depends on, echoes, or cleverly twists the wording or meaning of another expression.
-
B.
lyricsWordplay
Indicates a relationship where song lyrics employ puns, double meanings, or other forms of verbal playfulness.
-
C.
hasMultipleMeanings
Indicates that a term, symbol, or expression is associated with more than one distinct meaning or interpretation.
-
D.
hasMultilingualGlosses
Indicates that an entity is associated with glosses or explanatory labels available in multiple languages.
-
E.
isMultilingual
Indicates that an entity can understand and/or communicate in multiple languages.
- F. None of above. chosen
Provenance (4 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_69f3498280c48190bcc3494017d14234 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a00383e868c819098fd17e25fcbdb04 |
completed | May 10, 2026, 7:48 a.m. |
| PD | Predicate disambiguation | batch_6a0037cc59688190b7b9da939a413db3 |
completed | May 10, 2026, 7:46 a.m. |
| PDg | Predicate description generation | batch_6a00383d83c08190af7bc00f17affd97 |
completed | May 10, 2026, 7:48 a.m. |
Created at: May 1, 2026, 1:42 a.m.