Triple
T31816659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Types of Men |
E812153
|
entity |
| Predicate | proposesNumberOfTypes |
P180265
|
FINISHED |
| Object | six |
—
|
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: six | Statement: [Types of Men, proposesNumberOfTypes, six]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: proposesNumberOfTypes Context triple: [Types of Men, proposesNumberOfTypes, six]
-
A.
hasNumberOfTypes
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.
hasApproximateNumberOfVarieties
Indicates that an entity is associated with an estimated or non-exact count of different varieties or types.
-
D.
numberOfPropositions
Indicates the total count of distinct propositions associated with or contained within a given entity or context.
-
E.
typicalNumberOfSelections
Indicates the usual or expected count of selections made in a given choice or selection process.
- 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_69f348e846c081908eb468a0665afd55 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f739a638748190808e7a2930dce16e |
completed | May 3, 2026, 12:03 p.m. |
| PD | Predicate disambiguation | batch_69f732f2dc6c8190a4e86da98cc5eb05 |
completed | May 3, 2026, 11:35 a.m. |
| PDg | Predicate description generation | batch_69f739a58b3c81908abc2b8738a65678 |
completed | May 3, 2026, 12:03 p.m. |
Created at: April 30, 2026, 11:44 p.m.