Triple
T11320970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S&P BSE SENSEX |
E268091
|
entity |
| Predicate | regularTradingSession |
P2917
|
FINISHED |
| Object | 09:15–15:30 IST |
—
|
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: 09:15–15:30 IST | Statement: [S&P BSE SENSEX, regularTradingSession, 09:15–15:30 IST]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regularTradingSession Context triple: [S&P BSE SENSEX, regularTradingSession, 09:15–15:30 IST]
-
A.
hasTradingSession
Indicates that an entity participates in or is associated with a specific trading session or period during which trading activities occur.
-
B.
hasRegularMarket
Indicates that an entity maintains a recurring, scheduled marketplace or trading event where goods or services are regularly bought and sold.
-
C.
tradingHoursType
Indicates the classification of an entity’s trading hours, such as whether they are regular, extended, holiday-specific, or of another defined type.
-
D.
hasTradingHours
chosen
Indicates that an entity operates or is available for trading during specified time periods.
-
E.
tradingSegment
Indicates that one entity operates within, or is associated with, a specific trading segment or market subdivision for transactional activities.
- 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_69d6aaca5c24819083db46a30d86cb34 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9dff37081909622623e66e17ccd |
completed | April 9, 2026, 6:03 p.m. |
| PD | Predicate disambiguation | batch_69d787ad575081908274280bf75d95fd |
completed | April 9, 2026, 11:04 a.m. |
Created at: April 8, 2026, 9:32 p.m.