Triple
T9544201
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Russell Midcap Index |
E230239
|
entity |
| Predicate | typicalConstituentCountRange |
P5741
|
FINISHED |
| Object | approximately 800 |
—
|
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: approximately 800 | Statement: [Russell Midcap Index, typicalConstituentCountRange, approximately 800]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalConstituentCountRange Context triple: [Russell Midcap Index, typicalConstituentCountRange, approximately 800]
-
A.
numberOfConstituents
chosen
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.
typicalMembers
Indicates that the related entities are representative or characteristic members of a larger group, category, or class.
-
D.
typicalNumberOfVoices
Indicates the usual or characteristic number of distinct voices or parts involved in performing or realizing something (such as a musical work or texture).
-
E.
previousNumberOfConstituents
Indicates the number of constituents an entity had at an earlier point in time, before its current state.
- 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_69ca847c70b8819088a0a0bad64a50d6 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd98ebd4148190b71b134d7545fe35 |
completed | April 1, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69ccd58bd21881908b860e3ee469af13 |
completed | April 1, 2026, 8:21 a.m. |
Created at: March 30, 2026, 8:01 p.m.