Triple
T5828395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Tale of Mrs. Tiggy-Winkle |
E129284
|
entity |
| Predicate | hasPhysicalFormat |
P53051
|
FINISHED |
| Object | small-format gift book |
—
|
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: small-format gift book | Statement: [The Tale of Mrs. Tiggy-Winkle, hasPhysicalFormat, small-format gift book]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPhysicalFormat Context triple: [The Tale of Mrs. Tiggy-Winkle, hasPhysicalFormat, small-format gift book]
-
A.
hasPhysicalMedium
chosen
Indicates that one entity serves as the tangible carrier or material form through which another entity exists, is stored, or is transmitted.
-
B.
hasProductionFormat
Indicates that an entity is associated with, or presented in, a particular production or media format.
-
C.
hasDigitalForm
Indicates that something exists or is available in a digital or electronic format.
-
D.
hasExhibitFormat
Indicates the specific format or medium in which an exhibit is presented or made available.
-
E.
hasPublishingFormat
Indicates that an entity is associated with a specific format or medium in which it is published or made publicly available.
- 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_69c00849d55481908b4f9f5543e0bf6d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c044ab0a048190b84be40fb13c0f50 |
completed | March 22, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69c03341e5888190a5f219b6f92cb161 |
completed | March 22, 2026, 6:21 p.m. |
Created at: March 22, 2026, 3:53 p.m.