Triple
T13569465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spellmonger |
E324118
|
entity |
| Predicate | hasMultipleBooks |
P5481
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Spellmonger, hasMultipleBooks, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMultipleBooks Context triple: [Spellmonger, hasMultipleBooks, yes]
-
A.
hasThreeBooksWith
Indicates that two entities are related by one having exactly three books together with the other (e.g., jointly owned, shared, or associated as a group of three books).
-
B.
hasBook
Indicates that an entity possesses, owns, or is associated with a particular book.
-
C.
numberOfBooks
chosen
Indicates the quantity of books associated with a given entity.
-
D.
containsBook
Indicates that one entity (typically a container or collection) includes a specific book as part of its contents.
-
E.
hasWrittenWorkType
Indicates that an entity (typically a written work) is associated with a specific type or category of written work (such as novel, article, report, etc.).
- 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_69d8076830b48190910a902bae5888e2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb00f5b8881908617f42d227ed137 |
completed | April 12, 2026, 2:45 p.m. |
| PD | Predicate disambiguation | batch_69dbae161a0481909f9d3f40ca4e0ac5 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:48 p.m.