Triple
T11597153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Slate |
E275033
|
entity |
| Predicate | typicalInteractionWithFredFlintstone |
P100530
|
FINISHED |
| Object | scolds Fred for workplace mishaps |
—
|
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: scolds Fred for workplace mishaps | Statement: [Mr. Slate, typicalInteractionWithFredFlintstone, scolds Fred for workplace mishaps]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalInteractionWithFredFlintstone Context triple: [Mr. Slate, typicalInteractionWithFredFlintstone, scolds Fred for workplace mishaps]
-
A.
franchiseCharacter
Indicates a relationship where a character belongs to, appears in, or is part of a particular media franchise.
-
B.
relationshipWithBlondie
Indicates that there exists some form of relationship or connection between an entity and Blondie.
-
C.
relationshipWithSybilFawlty
Indicates the type or nature of a relationship that an entity has with Sybil Fawlty.
-
D.
roleOfMitchMitchell
Indicates that the specified role or function is held or performed by Mitch Mitchell.
-
E.
hasFictionalFamily
Indicates that an entity is associated with a family that exists only within a fictional or imaginary context.
- 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_69d6aae6b14c81908dc5a74bad7591f9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d89549c870819086e16e9110bbad87 |
completed | April 10, 2026, 6:14 a.m. |
| PD | Predicate disambiguation | batch_69d85dd20d188190863d1190d4c16048 |
completed | April 10, 2026, 2:17 a.m. |
| PDg | Predicate description generation | batch_69d87f2e67108190ac36bf47aac12fa8 |
completed | April 10, 2026, 4:40 a.m. |
Created at: April 8, 2026, 9:38 p.m.