Triple
T24269898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilshire 5000 Total Market Index |
E605248
|
entity |
| Predicate | marketCoverageType |
P30754
|
FINISHED |
| Object | total U.S. stock market |
—
|
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: total U.S. stock market | Statement: [Wilshire 5000 Total Market Index, marketCoverageType, total U.S. stock market]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marketCoverageType Context triple: [Wilshire 5000 Total Market Index, marketCoverageType, total U.S. stock market]
-
A.
marketSegmentCoverage
chosen
Indicates the extent to which a product, service, or campaign reaches or serves the intended market segment(s).
-
B.
marketCovered
Indicates that one entity’s products or services are already available or served within the geographic or customer market associated with another entity.
-
C.
regionCoverage
Indicates that one entity geographically spans, includes, or serves the area defined by another entity.
-
D.
dataCoverage
Indicates the extent or proportion of relevant data that is included, captured, or represented within a given dataset or system.
-
E.
geographicCoverageType
Indicates the type or nature of the geographic area that something covers or applies to.
- 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.