Triple
T9825340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank Booth |
E238639
|
entity |
| Predicate | speaksCatchphrase |
P74838
|
FINISHED |
| Object | “Baby wants to fuck” |
—
|
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: “Baby wants to fuck” | Statement: [Frank Booth, speaksCatchphrase, “Baby wants to fuck”]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: speaksCatchphrase Context triple: [Frank Booth, speaksCatchphrase, “Baby wants to fuck”]
-
A.
characterCatchphrase
chosen
Indicates that a particular phrase is commonly and distinctively used by a character as their catchphrase.
-
B.
openingCatchphrase
Indicates that one entity is a characteristic phrase or line regularly used by another entity at the beginning of a recurring performance, appearance, or communication.
-
C.
speaksWith
Indicates that one entity engages in spoken communication or conversation with another entity.
-
D.
featuresCatchphrase
Indicates that an entity prominently includes or is associated with a particular catchphrase.
-
E.
speaksIn
Indicates that an entity uses or expresses itself in a particular language or medium when speaking.
- 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_69ca84e0dd1881909800765d1e21f735 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3181c688190afea3b27ee392a30 |
completed | April 2, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69cd03e01ea881909a7d93fc3994ace5 |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:31 p.m.