Triple
T13564782
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peppermint Patty |
E324005
|
entity |
| Predicate | relationshipToSnoopy |
P107802
|
FINISHED |
| Object | believes Snoopy is a funny-looking kid |
—
|
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: believes Snoopy is a funny-looking kid | Statement: [Peppermint Patty, relationshipToSnoopy, believes Snoopy is a funny-looking kid]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToSnoopy Context triple: [Peppermint Patty, relationshipToSnoopy, believes Snoopy is a funny-looking kid]
-
A.
relationshipToPeppermintPatty
chosen
Indicates the specific type of personal or social relationship an entity has with Peppermint Patty.
-
B.
relationshipToSophie
Indicates the specific type of personal or social connection that an entity has to Sophie.
-
C.
relationshipToCreature
Indicates a specified type of relational connection that one entity has toward a particular creature.
-
D.
relationshipToBenjy
Indicates the specific type of relationship or connection an entity has to Benjy.
-
E.
relationshipToHenry
Indicates the specific type of relationship or connection that an entity has to Henry.
- 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_69d8076830b48190910a902bae5888e2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb00cecd48190a9a2caff3d424817 |
completed | April 12, 2026, 2:45 p.m. |
| PD | Predicate disambiguation | batch_69dbae161a0481909f9d3f40ca4e0ac5 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:47 p.m.