Triple
T31891978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Russell 2000 Value Index |
E814168
|
entity |
| Predicate | componentCountBasis |
P192067
|
FINISHED |
| Object | subset of approximately 2000 small-cap stocks |
—
|
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: subset of approximately 2000 small-cap stocks | Statement: [Russell 2000 Value Index, componentCountBasis, subset of approximately 2000 small-cap stocks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: componentCountBasis Context triple: [Russell 2000 Value Index, componentCountBasis, subset of approximately 2000 small-cap stocks]
-
A.
hasComponentCount
Indicates that an entity is associated with a specific number of components it contains or comprises.
-
B.
typicalNumberOfComponents
Indicates the usual or standard count of distinct components that an entity is expected to have.
-
C.
dimensionOfComponents
Indicates that a specified dimension value is associated with, or applies to, the components of an object or system.
-
D.
basisVectorsCount
Indicates the number of basis vectors associated with a given vector space or basis.
-
E.
numberOfConstituents
Indicates the total count of individual components or members that make up a larger whole or group.
- 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_69f348ef817481908440e2250319bcc8 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fcf36d2894819089b7db8e91b63c9d |
completed | May 7, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69fcf25c0a108190bfa823474098640b |
completed | May 7, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69fcf36bb86c8190a0a0ccf47cb56e5c |
completed | May 7, 2026, 8:17 p.m. |
Created at: April 30, 2026, 11:58 p.m.