Triple
T14923606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | COMBO-17 survey |
E371575
|
entity |
| Predicate | usesNumberOfFilters |
P38758
|
FINISHED |
| Object | 17 |
—
|
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: 17 | Statement: [COMBO-17 survey, usesNumberOfFilters, 17]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesNumberOfFilters Context triple: [COMBO-17 survey, usesNumberOfFilters, 17]
-
A.
numberOfFilters
chosen
Indicates the count of filters associated with or applied to a given entity or operation.
-
B.
usesFilter
Indicates that one entity applies or employs a filter (such as a criterion, condition, or processing mechanism) to another entity or set of data.
-
C.
hasFilterType
Indicates that an entity is associated with, or constrained by, a specific type or category of filter applied to it.
-
D.
hasNumberOfConditions
Indicates that an entity is associated with a specific count of conditions it has or is subject to.
-
E.
hasNumberOfRules
Indicates the specific count of rules associated with or applicable to an entity.
- 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_69d85cc7ea3481908228b5acb7d06f12 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6323f8c8190af02d06352d459c3 |
completed | April 15, 2026, 12:05 a.m. |
| PD | Predicate disambiguation | batch_69de9a52ba988190a26e268b4ea083ea |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:34 a.m.