Triple
T5707578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Tale of Benjamin Bunny |
E125821
|
entity |
| Predicate | hasPhysicalSetting |
P3538
|
FINISHED |
| Object | vegetable garden |
—
|
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: vegetable garden | Statement: [The Tale of Benjamin Bunny, hasPhysicalSetting, vegetable garden]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPhysicalSetting Context triple: [The Tale of Benjamin Bunny, hasPhysicalSetting, vegetable garden]
-
A.
hasPhysicalNature
Indicates that one entity possesses or exhibits a specific physical form, composition, or material nature in relation to another.
-
B.
hasSetting
chosen
Indicates that an entity takes place, occurs, or exists within a particular environment, context, or location.
-
C.
isPhysicalArtifact
Indicates that the subject is a tangible, man-made object that physically exists in the real world.
-
D.
hasPhysicalFootprint
Indicates that one entity occupies or affects a specific physical area or space in the real world.
-
E.
hasPhysicalMedium
Indicates that one entity serves as the tangible carrier or material form through which another entity exists, is stored, or is transmitted.
- 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_69c0082d6fe48190b777fb383769e5c8 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c024892fd88190a91133fc88365410 |
completed | March 22, 2026, 5:19 p.m. |
| PD | Predicate disambiguation | batch_69c021c2d8bc8190b947c7d1f423d2f3 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:45 p.m.