Triple
T33682375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Sacred Harp |
E862935
|
entity |
| Predicate | numberOfShapes |
P204189
|
FINISHED |
| Object | 4-shape system |
—
|
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-shape system | Statement: [The Sacred Harp, numberOfShapes, 4-shape system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfShapes Context triple: [The Sacred Harp, numberOfShapes, 4-shape system]
-
A.
numberOfSides
Indicates the relationship that specifies how many sides a given object or shape has.
-
B.
significantlyShapes
Indicates that one entity has a strong, influential impact on determining or altering the nature, outcome, or development of another entity.
-
C.
numberOfCurves
Indicates the relationship that specifies how many distinct curves are associated with or contained in a given entity.
-
D.
numberOfCounts
Indicates the total quantity or tally of discrete occurrences, items, or instances associated with an entity or event.
-
E.
numberOfFiguresDepicted
Indicates the total count of distinct figures shown within a given depiction or representation.
- 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_69f3498662b48190904442c39df84fb7 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a034540e37c819087a5c75c559323d8 |
completed | May 12, 2026, 3:20 p.m. |
| PD | Predicate disambiguation | batch_6a0344e26fec8190867227f9692e92df |
completed | May 12, 2026, 3:18 p.m. |
| PDg | Predicate description generation | batch_6a0345400778819081fb3b5b71336cd7 |
completed | May 12, 2026, 3:20 p.m. |
Created at: May 1, 2026, 1:43 a.m.