Triple
T7912746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Russell 1000 Value Index |
E183737
|
entity |
| Predicate | styleBoxCategory |
P79746
|
FINISHED |
| Object | large value |
—
|
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: large value | Statement: [Russell 1000 Value Index, styleBoxCategory, large value]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: styleBoxCategory Context triple: [Russell 1000 Value Index, styleBoxCategory, large value]
-
A.
styleCategory
Indicates the stylistic classification or genre category that an item, work, or entity belongs to.
-
B.
bodyStyleCategory
Indicates the general body style classification or category that an item (such as a vehicle or product) belongs to.
-
C.
structureStyle
Indicates the architectural or design style characterizing how a structure is built or formed.
-
D.
structuralStyle
Indicates the architectural or design style that characterizes the structure or form of an entity.
-
E.
uniformCategory
Indicates that two or more entities share the same classification or type within a defined category system.
- 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_69ca828dec0c81908b8f55a4dbbb53ff |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a7383cc819084eab19799209d2e |
completed | March 31, 2026, 3:07 a.m. |
| PD | Predicate disambiguation | batch_69cae92f9498819085277879e59aa072 |
completed | March 30, 2026, 9:20 p.m. |
| PDg | Predicate description generation | batch_69caf7882b048190baa333af9f698590 |
completed | March 30, 2026, 10:22 p.m. |
Created at: March 30, 2026, 5:04 p.m.