Triple
T22788049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oh Be A Fine Girl/Guy, Kiss Me |
E564026
|
entity |
| Predicate | componentForLetterO |
P78796
|
FINISHED |
| Object | Oh |
—
|
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: Oh | Statement: [Oh Be A Fine Girl/Guy, Kiss Me, componentForLetterO, Oh]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: componentForLetterO Context triple: [Oh Be A Fine Girl/Guy, Kiss Me, componentForLetterO, Oh]
-
A.
componentRepresents
Indicates that one component stands in for, symbolizes, or models another entity or concept within a system or context.
-
B.
isOandO
Indicates a relationship where one entity is both an originator and an owner (O&O) of another entity, such as content, data, or a resource.
-
C.
componentCharacter1
chosen
Indicates that one entity is the first (primary) character component or constituent part of another entity.
-
D.
orthographicPattern
Indicates a relationship where entities share or follow a specific arrangement of written symbols, such as spelling or letter patterns.
-
E.
usesSpecialLetterFor
Indicates that one entity employs a particular special letter or character specifically in relation to 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_69e2455500788190b4b33030461f3bbd |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17c32de6481909ef358d16de98496 |
completed | April 29, 2026, 3:34 a.m. |
| PD | Predicate disambiguation | batch_69eed2c32e8c8190b73bb9965ed47d64 |
completed | April 27, 2026, 3:06 a.m. |
Created at: April 17, 2026, 3:29 p.m.