Triple
T58043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chicago Stock Exchange |
E1148
|
entity |
| Predicate | hasPreMarketSession |
P2824
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Chicago Stock Exchange, hasPreMarketSession, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPreMarketSession Context triple: [Chicago Stock Exchange, hasPreMarketSession, yes]
-
A.
hasStockExchange
Indicates that an entity is associated with or listed on a particular stock exchange.
-
B.
canBeCalledIntoSpecialSessionBy
Indicates that one entity has the authority to convene or summon another entity into a special session.
-
C.
marketPosition
Indicates the relative standing or rank an entity holds within a specific market compared to its competitors.
-
D.
hasSession
Indicates that an entity is associated with, participates in, or contains a particular session instance.
-
E.
isMostTradedCurrency
Indicates that a currency is the one with the highest trading volume or frequency in a given market or context.
- 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.