Triple
T58030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chicago Stock Exchange |
E1148
|
entity |
| Predicate | hasMarketParticipants |
P2823
|
FINISHED |
| Object | broker-dealers |
—
|
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: broker-dealers | Statement: [Chicago Stock Exchange, hasMarketParticipants, broker-dealers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMarketParticipants Context triple: [Chicago Stock Exchange, hasMarketParticipants, broker-dealers]
-
A.
hasStakeholder
Indicates that an entity is a stakeholder of another entity, typically having an interest, involvement, or influence in its activities or outcomes.
-
B.
hasPartner
Indicates that one entity is in a partner relationship (such as romantic, life, or business partnership) with another entity.
-
C.
hasAudience
Indicates that an entity is intended to be received, viewed, or engaged with by a particular group of people.
-
D.
targetMarket
Indicates the group of consumers or organizations that a product, service, or campaign is specifically intended and designed to reach.
-
E.
numberOfParticipants
Indicates the total count of entities involved in a particular event, activity, or relationship.
- 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_69a248adc5b48190aa8db9fb092fb28a |
completed | Feb. 28, 2026, 1:45 a.m. |
| NER | Named-entity recognition | batch_69a24b915c9881908c798f4dacb39f1d |
completed | Feb. 28, 2026, 1:57 a.m. |
| PD | Predicate disambiguation | batch_69a24ac6799c8190b508933acc0a4c7d |
completed | Feb. 28, 2026, 1:54 a.m. |
| PDg | Predicate description generation | batch_69a24b90ab24819085478dbe95f717dd |
completed | Feb. 28, 2026, 1:57 a.m. |
Created at: Feb. 28, 2026, 1:50 a.m.