Triple
T13619476
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seven Dreams: A Book of North American Landscapes |
E325409
|
entity |
| Predicate | numberOfPlannedVolumes |
P2734
|
FINISHED |
| Object | 7 |
—
|
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: 7 | Statement: [Seven Dreams: A Book of North American Landscapes, numberOfPlannedVolumes, 7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPlannedVolumes Context triple: [Seven Dreams: A Book of North American Landscapes, numberOfPlannedVolumes, 7]
-
A.
numberOfVolumes
chosen
Indicates the total count of separate volumes or parts that make up a multi-volume work or collection.
-
B.
numberPlanned
Indicates that a specific quantity has been scheduled or intended for a future action or allocation.
-
C.
numberOfRulesPlanned
Indicates the planned or intended count of rules associated with an entity or process.
-
D.
plannedNumberOfTests
Indicates the total count of tests that are intended or scheduled to be conducted for a given context or period.
-
E.
expectedDataVolume
Indicates the anticipated amount of data that should be produced, transferred, or stored in the context of the specified relationship or process.
- 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_69d8076aae28819092cf636190ee5529 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbbb9ee3f081909056dc1a92c40b7a |
completed | April 12, 2026, 3:34 p.m. |
| PD | Predicate disambiguation | batch_69dbae1b3ee481909bd43ded6227a3e5 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:50 p.m.