Triple
T37229658
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norville Rogers |
E923095
|
entity |
| Predicate | hasPetLikeCompanion |
P189712
|
FINISHED |
| Object | Scooby-Doo |
—
|
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: Scooby-Doo | Statement: [Norville Rogers, hasPetLikeCompanion, Scooby-Doo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPetLikeCompanion Context triple: [Norville Rogers, hasPetLikeCompanion, Scooby-Doo]
-
A.
hasAnimal
Indicates that one entity possesses, keeps, or is associated with an animal.
-
B.
hasFictionalPet
Indicates that an entity has, owns, or is associated with a pet that is fictional or imaginary.
-
C.
hasAnimalCollection
Indicates that one entity possesses or maintains a collection or group of animals associated with it.
-
D.
hasPetInterest
Indicates that one entity has an interest in, affinity for, or concern about pets in relation to another entity or context.
-
E.
hasFictionalCompanion
chosen
Indicates that one entity has another entity as its fictional companion, typically within a narrative or imaginative context.
- 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_69f76ea7f0008190b31b8e30f3d05a71 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fe991bca608190b524e419642f4243 |
completed | May 9, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69fe979fc1c4819091fc48d63ea12063 |
completed | May 9, 2026, 2:10 a.m. |
Created at: May 3, 2026, 4:15 p.m.