Triple
T8492523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Search by the Mule |
E201006
|
entity |
| Predicate | partOfBook |
P83018
|
FINISHED |
| Object | Second Foundation first half |
—
|
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: Second Foundation first half | Statement: [Search by the Mule, partOfBook, Second Foundation first half]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfBook Context triple: [Search by the Mule, partOfBook, Second Foundation first half]
-
A.
partOfLibrary
Indicates that one entity is a component, section, or item belonging to or contained within a library.
-
B.
chapterType
Indicates the specific kind or category of a chapter within a larger work or document.
-
C.
chapterOn
Indicates that one entity (typically a chapter) is about, discusses, or focuses on the subject represented by another entity.
-
D.
book7Content
Indicates that an entity contains or represents the content of book 7 in a series or collection.
-
E.
chapterBefore
Indicates that one chapter occurs earlier in sequence or order than another chapter.
- F. None of above. chosen
Provenance (4 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_69ca831ee390819095fae73400bbfafc |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe55cf5dc81908cad31ac53e15b46 |
completed | March 31, 2026, 3:16 p.m. |
| PD | Predicate disambiguation | batch_69cbd10a4b0881909e254117780dc823 |
completed | March 31, 2026, 1:50 p.m. |
| PDg | Predicate description generation | batch_69cbe30d453481908f897ed2b06e7534 |
completed | March 31, 2026, 3:06 p.m. |
Created at: March 30, 2026, 6:13 p.m.