Triple
T27874805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teddy Valiant |
E704897
|
entity |
| Predicate | relationshipToToons |
P200618
|
FINISHED |
| Object | victim of Toon violence |
—
|
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: victim of Toon violence | Statement: [Teddy Valiant, relationshipToToons, victim of Toon violence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToToons Context triple: [Teddy Valiant, relationshipToToons, victim of Toon violence]
-
A.
relationshipToCharacter
Indicates the specific type of personal, social, or narrative connection that one entity has to a given character.
-
B.
relationshipToMickey
Indicates the specific familial, social, or other personal connection that one entity has to Mickey.
-
C.
relationshipToTony
Indicates the specific type of relationship or connection that an entity has with Tony.
-
D.
relationshipToEdd
Indicates the specific type of relationship or connection that an entity has to Edd.
-
E.
playerRelations
Indicates the nature or status of the relationship between players, such as alliances, rivalries, or other interpersonal dynamics.
- 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_69ef84111bb4819084298f994b31c62f |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69ff9bed58dc8190a204816d4ed6c32c |
completed | May 9, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69ff9b69653c81908ab0d88055a66a88 |
completed | May 9, 2026, 8:39 p.m. |
| PDg | Predicate description generation | batch_69ff9bec9d748190869caebf6bf0c78f |
completed | May 9, 2026, 8:41 p.m. |
Created at: April 27, 2026, 6:26 p.m.