Triple
T33125111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Book II (Finnegans Wake) |
E847699
|
entity |
| Predicate | numberOfMajorDivisionsInWork |
P1905
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Book II (Finnegans Wake), numberOfMajorDivisionsInWork, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMajorDivisionsInWork Context triple: [Book II (Finnegans Wake), numberOfMajorDivisionsInWork, 4]
-
A.
hasNumberOfDivisions
chosen
Indicates the relationship that specifies how many divisions or subunits an entity possesses.
-
B.
numberOfMajorProjects
Indicates the count of significant or primary projects associated with an entity.
-
C.
isMajorDivisionOf
Indicates that one entity is a primary or principal subdivision or section within another, larger entity.
-
D.
numberOfMajorRevisions
Indicates the count of significant revision events that have occurred for an entity.
-
E.
hasDivisionLevel
Indicates that one entity is associated with a specific hierarchical or organizational division level of another entity.
- 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_69f349588f088190b7c9588860f72033 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a02ff7de1d881909c29729f2a771381 |
completed | May 12, 2026, 10:22 a.m. |
| PD | Predicate disambiguation | batch_6a02fd1c45c48190bf9dbd91acaeee9f |
completed | May 12, 2026, 10:12 a.m. |
Created at: May 1, 2026, 1:27 a.m.