Triple
T36918639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Club Dumas |
E913116
|
entity |
| Predicate | containsFictionalBook |
P197301
|
FINISHED |
| Object | De Umbrarum Regni Novem Portis |
—
|
NE NERFINISHED |
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: De Umbrarum Regni Novem Portis | Statement: [The Club Dumas, containsFictionalBook, De Umbrarum Regni Novem Portis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsFictionalBook Context triple: [The Club Dumas, containsFictionalBook, De Umbrarum Regni Novem Portis]
-
A.
hasFictionalContent
Indicates that something contains or includes material that is imaginary, invented, or not intended to represent real events or facts.
-
B.
hasFictionalDocument
chosen
Indicates that one entity possesses, is associated with, or includes a document that is fictional or exists only within an imagined or narrative context.
-
C.
hasFictionComponent
Indicates that something includes, contains, or is composed in part of a fictional element or work.
-
D.
hasFictionalType
Indicates that an entity is associated with or classified under a particular type or category that is fictional rather than real.
-
E.
containsBook
Indicates that one entity (typically a container or collection) includes a specific book as part of its contents.
- 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_69f76e885b848190bad82c87e9525486 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a015ff02814819094806517fc4c69fa |
completed | May 11, 2026, 4:49 a.m. |
| PD | Predicate disambiguation | batch_6a0154ddd3c48190b85f9f48731cfd8f |
completed | May 11, 2026, 4:02 a.m. |
Created at: May 3, 2026, 4:13 p.m.