Triple
T29642064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George |
E755886
|
entity |
| Predicate | bookSeriesType |
P75058
|
FINISHED |
| Object | popular science for children |
—
|
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: popular science for children | Statement: [George, bookSeriesType, popular science for children]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bookSeriesType Context triple: [George, bookSeriesType, popular science for children]
-
A.
literarySeriesType
chosen
Indicates the specific kind or category of a literary series that an entity belongs to or is characterized as.
-
B.
hasNumberOfBooksInSeries
Indicates the quantity of books that belong to a particular series.
-
C.
documentsSeries
Indicates that one document belongs to, or is part of, a larger series of related documents.
-
D.
literarySeriesGenre
Indicates that a literary series belongs to or is categorized under a particular genre.
-
E.
literarySeries
Indicates that one work is part of, or belongs to, a larger literary series that connects multiple related works.
- 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_69f0ef89d2c88190a6d0d5116ccd7cc9 |
completed | April 28, 2026, 5:34 p.m. |
| NER | Named-entity recognition | batch_69f66ed0653c819085adda918bd12f83 |
completed | May 2, 2026, 9:38 p.m. |
| PD | Predicate disambiguation | batch_69f6659d36208190b01412600a4ed57d |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 28, 2026, 6:47 p.m.