Triple
T32192121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kanamits |
E822283
|
entity |
| Predicate | bookContent |
P16933
|
FINISHED |
| Object | cookbook for preparing humans |
—
|
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: cookbook for preparing humans | Statement: [Kanamits, bookContent, cookbook for preparing humans]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bookContent Context triple: [Kanamits, bookContent, cookbook for preparing humans]
-
A.
book5Content
chosen
Indicates that one entity is the content or textual material contained within the book represented by the other entity.
-
B.
Book1Content
Indicates that one entity is the content (text, material, or subject matter) contained within a specific book entity.
-
C.
book7Content
Indicates that an entity contains or represents the content of book 7 in a series or collection.
-
D.
book1Contains
Indicates that one book includes, encloses, or has as part of its content another specified element or section.
-
E.
book
Indicates that an agent reserves or schedules a service, event, or resource for future use.
- 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_69f3490819cc81909bae1f8ce99423c5 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6bace6c508190a7b25ad1024151b6 |
completed | May 3, 2026, 3:02 a.m. |
| PD | Predicate disambiguation | batch_69f6b3aa892481908d29283a074e6722 |
completed | May 3, 2026, 2:32 a.m. |
Created at: May 1, 2026, 12:35 a.m.