Triple
T31924943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cornelia Bullock |
E815076
|
entity |
| Predicate | hiresAsButler |
P4079
|
FINISHED |
| Object | Godfrey |
—
|
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: Godfrey | Statement: [Cornelia Bullock, hiresAsButler, Godfrey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hiresAsButler Context triple: [Cornelia Bullock, hiresAsButler, Godfrey]
-
A.
hasServant
chosen
Indicates that one entity has another entity serving it in a subordinate or attendant role.
-
B.
roleInTheGrandBudapestHotel
Indicates that an entity has a specific role or part in the context of "The Grand Budapest Hotel" (such as a character, performer, or production role).
-
C.
servesAtThePleasureOf
Indicates that one entity holds a position or role that can be terminated at any time by another entity, typically at the discretion or will of that other entity.
-
D.
servedAsLadyInWaitingTo
Indicates that one person held the role of lady-in-waiting in service to another, typically a female member of royalty or nobility.
-
E.
servantType
Indicates the specific role or category of service that one entity performs in relation to another.
- 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_69f348f1df848190851bbfb988da3414 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b1fabffc81909d345f47c6692073 |
completed | May 3, 2026, 2:24 a.m. |
| PD | Predicate disambiguation | batch_69f6aca7081881909e96a8b05ec086bb |
completed | May 3, 2026, 2:02 a.m. |
Created at: May 1, 2026, 12:03 a.m.