Triple
T29136320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wrecker |
E738519
|
entity |
| Predicate | favoriteObjectType |
P166356
|
FINISHED |
| Object | stuffed tooka doll |
—
|
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: stuffed tooka doll | Statement: [Wrecker, favoriteObjectType, stuffed tooka doll]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: favoriteObjectType Context triple: [Wrecker, favoriteObjectType, stuffed tooka doll]
-
A.
favoriteObject
chosen
Indicates that one entity is the preferred or most liked object of another entity.
-
B.
typicalObjectType
Indicates that something is a common or characteristic type of object typically associated with or involved in another entity or situation.
-
C.
primaryTargetType
Indicates the main category or type of entity that is the principal focus or intended recipient of an action, effect, or operation.
-
D.
favoriteObjectsToCount
Indicates that an entity has particular objects it prefers or most commonly chooses when performing counting activities.
-
E.
oreType
Indicates the specific kind or classification of ore associated with an entity.
- 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_69f07cb3adb48190a9e0e169cd026634 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f6626ac7508190959be92ac34c33ac |
completed | May 2, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69f660f082508190a95a7888ad66cb2e |
completed | May 2, 2026, 8:39 p.m. |
Created at: April 28, 2026, 11:34 a.m.