Triple
T27781670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Beautician and the Beast |
E699347
|
entity |
| Predicate | hasTimothyDaltonRole |
P177115
|
FINISHED |
| Object | Boris Pochenko |
—
|
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: Boris Pochenko | Statement: [The Beautician and the Beast, hasTimothyDaltonRole, Boris Pochenko]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTimothyDaltonRole Context triple: [The Beautician and the Beast, hasTimothyDaltonRole, Boris Pochenko]
-
A.
successorAsJamesBond
Indicates that one entity took over the role of portraying James Bond from another entity.
-
B.
associatedWithActorPlayingBond
Indicates that one entity has a relationship or connection with an actor who has played the character James Bond.
-
C.
hasJoanFontaineRole
Indicates that an entity has a role played by Joan Fontaine in a film, television, or theatrical production.
-
D.
numberOfJamesBondFilmsStarring
Indicates the count of James Bond films in which a specified actor (or entity) appeared in the starring role.
-
E.
relationshipToJamesBond
Indicates the specific familial, romantic, professional, or social relationship that one entity has to James Bond.
- 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_69ef6a4b5a9081909c9111396c2be3d2 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f6f85bfba48190aba95b40642a8ca7 |
completed | May 3, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69f6f65fd1d08190b88e5e68ba268500 |
completed | May 3, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69f6f854486c81909396d944a55e03ab |
completed | May 3, 2026, 7:25 a.m. |
Created at: April 27, 2026, 5:10 p.m.