Triple
T31133017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Belvedere Goes to College |
E793561
|
entity |
| Predicate | featuresFictionalButler |
P202112
|
FINISHED |
| Object | Lynn Belvedere |
—
|
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: Lynn Belvedere | Statement: [Mr. Belvedere Goes to College, featuresFictionalButler, Lynn Belvedere]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresFictionalButler Context triple: [Mr. Belvedere Goes to College, featuresFictionalButler, Lynn Belvedere]
-
A.
characterRoleOfJeeves
Indicates that the subject is the narrative or fictional role played by the character Jeeves.
-
B.
describedAsByBertieWooster
Indicates that something is characterized or portrayed in a particular way by the character Bertie Wooster.
-
C.
uncleAlias
Indicates that one entity is an alternative name or label used to refer to an uncle relationship involving another entity.
-
D.
describedBySherlockHolmesAs
Indicates that one entity is characterized or depicted in a particular way by Sherlock Holmes.
-
E.
featuresHouseElf
Indicates that something includes or prominently involves a house elf as part of its content or composition.
- 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_69f224d1701c819094f429798290e361 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a005247dba08190acadf962bcefe4a0 |
completed | May 10, 2026, 9:39 a.m. |
| PD | Predicate disambiguation | batch_6a00519029848190a234358dfba45084 |
completed | May 10, 2026, 9:36 a.m. |
| PDg | Predicate description generation | batch_6a00524723408190b0294e87e5cf7715 |
completed | May 10, 2026, 9:39 a.m. |
Created at: April 29, 2026, 9:05 p.m.