Triple
T30079975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | If U Seek Amy |
E764426
|
entity |
| Predicate | doubleEntendrePhrase |
P8493
|
FINISHED |
| Object | If you seek Amy ≈ F-U-C-K me |
—
|
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: If you seek Amy ≈ F-U-C-K me | Statement: [If U Seek Amy, doubleEntendrePhrase, If you seek Amy ≈ F-U-C-K me]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: doubleEntendrePhrase Context triple: [If U Seek Amy, doubleEntendrePhrase, If you seek Amy ≈ F-U-C-K me]
-
A.
meaningOfPhrase
chosen
Indicates that one entity expresses or defines the semantic content or interpretation of a given phrase.
-
B.
peutComprendre
Indicates that an entity has the ability or capacity to understand another entity or concept.
-
C.
containsFrenchPhrases
Indicates that the subject includes one or more phrases expressed in the French language.
-
D.
meaningViaRebecca
Indicates a relationship where something is understood, interpreted, or conveyed specifically through the mediation or perspective of Rebecca.
-
E.
hasLatinPhraseMeaning
Indicates that one entity is a Latin phrase that expresses the meaning or translation of another entity.
- 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_69f22472eee081909791dc372aa766e9 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f67d4086c08190ac65ff5d29fa06dc |
completed | May 2, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69f673c664f08190b4d66cdc305e10db |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 29, 2026, 7:02 p.m.