Triple
T28192351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Me So Horny |
E716350
|
entity |
| Predicate | sampledDialogueFrom |
P165431
|
FINISHED |
| Object | Full Metal Jacket |
—
|
NE NERFINISHED |
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: Full Metal Jacket | Statement: [Me So Horny, sampledDialogueFrom, Full Metal Jacket]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sampledDialogueFrom Context triple: [Me So Horny, sampledDialogueFrom, Full Metal Jacket]
-
A.
dialoguesBy
Indicates that one entity is the creator, author, or source of the dialogues associated with another entity.
-
B.
dialogueType
Indicates the specific kind or category of dialogue occurring between entities (e.g., question-answer, negotiation, instruction).
-
C.
dialogue
Indicates that two or more entities are engaged in an exchange of spoken or written communication with each other.
-
D.
hasDialogueIn
Indicates that an entity participates in or contains spoken or written dialogue within a specified context, such as a scene, work, or medium.
-
E.
dialogueFeature
Indicates that one entity exhibits or involves a particular characteristic, property, or element of a dialogue or conversational exchange with another entity.
- 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_69efd6b612f48190a72012b520afbd10 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f659355a208190be2609ffc7a9c427 |
completed | May 2, 2026, 8:06 p.m. |
| PD | Predicate disambiguation | batch_69f6575d89788190aca478e4aea05a65 |
completed | May 2, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69f65875030881909007c502b7dcc998 |
completed | May 2, 2026, 8:03 p.m. |
Created at: April 27, 2026, 10:26 p.m.