Triple
T24269910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilshire 5000 Total Market Index |
E605248
|
entity |
| Predicate | typicalConstituentCount |
P143118
|
FINISHED |
| Object | around 3500 to 4000 issues in recent years |
—
|
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: around 3500 to 4000 issues in recent years | Statement: [Wilshire 5000 Total Market Index, typicalConstituentCount, around 3500 to 4000 issues in recent years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalConstituentCount Context triple: [Wilshire 5000 Total Market Index, typicalConstituentCount, around 3500 to 4000 issues in recent years]
-
A.
numberOfConstituents
Indicates the total count of individual components or members that make up a larger whole or group.
-
B.
typicalConstituentType
Indicates the usual or characteristic type of component that typically makes up or forms part of something.
-
C.
numberOfConstituentsType
Indicates the type or category used to classify how many constituents (parts or members) are involved in or associated with something.
-
D.
typicalNumberOfComponents
chosen
Indicates the usual or standard count of distinct components that an entity is expected to have.
-
E.
usesConstituentsFrom
Indicates that one entity is composed of, incorporates, or is derived from specific constituent parts provided by another 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_69e2954707dc8190915551eb114cfff6 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f28d58666881909f28f4d4f0f7d590 |
completed | April 29, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69f1c450aa508190bc9d372a5f6ee47a |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 18, 2026, 12:07 a.m.