Triple
T12070595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bianchi classification |
E287411
|
entity |
| Predicate | numberOfTypes |
P76192
|
FINISHED |
| Object | 9 |
—
|
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: 9 | Statement: [Bianchi classification, numberOfTypes, 9]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTypes Context triple: [Bianchi classification, numberOfTypes, 9]
-
A.
hasNumberOfTypes
chosen
Indicates that an entity is associated with a specific count of distinct types or categories it possesses or includes.
-
B.
originalNumberOfTypes
Indicates the initial total count of distinct types that existed before any changes, filtering, or transformations were applied.
-
C.
numberOfConstituentsType
Indicates the type or category used to classify how many constituents (parts or members) are involved in or associated with something.
-
D.
numberOfCounts
Indicates the total quantity or tally of discrete occurrences, items, or instances associated with an entity or event.
-
E.
hasApproximateNumberOfVarieties
Indicates that an entity is associated with an estimated or non-exact count of different varieties or types.
- 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_69d6ab4846e081908ee7bbd66a6d3459 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9100b4ca8819084845ca4c13e34ce |
completed | April 10, 2026, 2:58 p.m. |
| PD | Predicate disambiguation | batch_69d902bda47c8190b94860b31df4a98c |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:48 p.m.