Triple
T15563935
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robinhood Markets, Inc. |
E371066
|
entity |
| Predicate | hasTradingFeature |
P92951
|
FINISHED |
| Object | fractional shares |
—
|
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: fractional shares | Statement: [Robinhood Markets, Inc., hasTradingFeature, fractional shares]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTradingFeature Context triple: [Robinhood Markets, Inc., hasTradingFeature, fractional shares]
-
A.
supportsTradingType
Indicates that one entity enables, allows, or is compatible with a specified type or mode of trading.
-
B.
hasTradingModel
Indicates that one entity uses, is governed by, or is associated with a particular trading model.
-
C.
hasTradeCharacteristic
chosen
Indicates that an entity possesses a specific trade-related attribute, quality, or feature.
-
D.
hasTradingVenueType
Indicates the specific category or type of trading venue associated with a given trading platform or marketplace.
-
E.
hasTrade
Indicates a relationship where one entity engages in or maintains a commercial exchange or trading activity with 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_69d85cc6cf40819091f4a5facee1ebe6 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ddc66448190948280fb0c8d390c |
completed | April 16, 2026, 2:47 a.m. |
| PD | Predicate disambiguation | batch_69deda7e6e748190b29ccce23298afef |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:10 a.m.