Triple
T9787762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bullseye |
E237530
|
entity |
| Predicate | toyTypeInUniverse |
P66481
|
FINISHED |
| Object | Woody's Roundup merchandise |
—
|
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: Woody's Roundup merchandise | Statement: [Bullseye, toyTypeInUniverse, Woody's Roundup merchandise]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: toyTypeInUniverse Context triple: [Bullseye, toyTypeInUniverse, Woody's Roundup merchandise]
-
A.
toyLine
Indicates that one entity is part of, or associated with, a particular toy product line or series.
-
B.
hasFictionalUniverseElement
Indicates that one entity is a component, feature, or constituent part of the fictional universe represented by the other entity.
-
C.
inUniverseType
Indicates that one entity exists within, or is categorized as belonging to, a particular fictional or conceptual universe type defined by the other entity.
-
D.
inUniverseProductType
chosen
Indicates that a product belongs to or is categorized within a specific fictional or defined universe or setting.
-
E.
hasFictionalUniverseProperty
Indicates that a fictional universe possesses a specific characteristic, attribute, or property.
- 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_69ca84da927881909bda80caecad6010 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda211b0608190bc8ceb905d02db83 |
completed | April 1, 2026, 10:54 p.m. |
| PD | Predicate disambiguation | batch_69cd03d77c6c81909b675955bf113320 |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:27 p.m.