Triple
T12855105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | spinning jenny |
E307429
|
entity |
| Predicate | numberOfSpindles |
P107228
|
FINISHED |
| Object | multiple |
—
|
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: multiple | Statement: [spinning jenny, numberOfSpindles, multiple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSpindles Context triple: [spinning jenny, numberOfSpindles, multiple]
-
A.
typicalSpindleCount
Indicates the usual or standard number of spindles associated with an entity in this relationship.
-
B.
shaftCount
Indicates the number of shafts associated with or contained in an object or system.
-
C.
numberOfSpokes
Indicates the count of individual spokes associated with or contained in a given object or structure.
-
D.
hasNumberOfSpokes
Indicates the relationship that specifies how many spokes are present in or associated with an object.
-
E.
numberOfRecordedMillsAndWheels
Indicates the total count of mills and wheels that have been recorded or documented for a given subject.
- 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_69d7bdf5e7cc8190be357278bc5ba3bb |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9714208f881908f7f8a921362909a |
completed | April 10, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69d96fa3002881908000357b1f95a3ac |
completed | April 10, 2026, 9:46 p.m. |
| PDg | Predicate description generation | batch_69d9713e45a88190acd346f066093550 |
completed | April 10, 2026, 9:53 p.m. |
Created at: April 9, 2026, 5:37 p.m.