Triple
T6797795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cinderella Service |
E156100
|
entity |
| Predicate | roleCharacterization |
P59266
|
FINISHED |
| Object | often-overlooked command |
—
|
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: often-overlooked command | Statement: [Cinderella Service, roleCharacterization, often-overlooked command]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleCharacterization Context triple: [Cinderella Service, roleCharacterization, often-overlooked command]
-
A.
roleCharacteristic
chosen
Indicates that a particular characteristic, quality, or attribute is associated with and helps define a given role or function.
-
B.
characterDescription
Indicates that one entity provides a textual description or portrayal of the characteristics, traits, or attributes of another entity.
-
C.
featuresCharacterRole
Indicates that a work includes a character appearing in a specific narrative or functional role.
-
D.
stagePersonaOf
Indicates a relationship where one entity is the staged or performed persona, role, or character representation of another entity.
-
E.
roleInText
Indicates that an entity participates in a text with a specific function or capacity (e.g., author, editor, character).
- 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_69c6881844448190a65822d9b39d7f88 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2ca0c288190a990180fb7cfd08f |
completed | March 27, 2026, 6:56 p.m. |
| PD | Predicate disambiguation | batch_69c6d099bf08819089a9f9894d037e74 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:15 p.m.