Triple
T10736121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cantigas de Santa Maria |
E253199
|
entity |
| Predicate | approximateNumberOfPieces |
P20105
|
FINISHED |
| Object | 427 |
—
|
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: 427 | Statement: [Cantigas de Santa Maria, approximateNumberOfPieces, 427]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateNumberOfPieces Context triple: [Cantigas de Santa Maria, approximateNumberOfPieces, 427]
-
A.
numberOfPieces
Indicates the quantity of discrete parts or units into which something is divided or composed.
-
B.
sectionCountApproximate
Indicates that the number of sections associated with an entity is known only approximately rather than as an exact count.
-
C.
hasApproximateNumberOfMiniatures
Indicates that an entity is associated with an estimated or non-exact count of miniatures.
-
D.
numberOfFragmentsApprox
chosen
Indicates an approximate count of how many fragments or pieces are associated with the subject.
-
E.
mineCountApproximate
Indicates that the number of mines associated with an entity is estimated or roughly counted rather than known exactly.
- 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_69d6aa5e51e8819095f06881cecf152e |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d71022aee0819091a5790d3dee6777 |
completed | April 9, 2026, 2:34 a.m. |
| PD | Predicate disambiguation | batch_69d6f309a44881908e49e3ba478c35b4 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:14 p.m.