Triple
T1653377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokyo Stock Exchange |
E35742
|
entity |
| Predicate | hasTradingSession |
P30924
|
FINISHED |
| Object | morning session |
—
|
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: morning session | Statement: [Tokyo Stock Exchange, hasTradingSession, morning session]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTradingSession Context triple: [Tokyo Stock Exchange, hasTradingSession, morning session]
-
A.
hasTradingHours
Indicates that an entity operates or is available for trading during specified time periods.
-
B.
hasPreMarketSession
Indicates that a financial instrument or market has a designated trading session that occurs before the regular market hours.
-
C.
hasTradingDays
Indicates that an entity is associated with specific days on which trading or commercial transactions are conducted.
-
D.
hasAfterHoursSession
Indicates that an entity conducts or participates in a session that takes place outside of regular or standard operating hours.
-
E.
tradingHoursType
Indicates the classification of an entity’s trading hours, such as whether they are regular, extended, holiday-specific, or of another defined type.
- 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_69a8860568888190a32cd9f70acbba42 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aaf3359ce48190803b322db8ad6027 |
completed | March 6, 2026, 3:31 p.m. |
| PD | Predicate disambiguation | batch_69a907cff53c8190b424f088478d3e2c |
completed | March 5, 2026, 4:34 a.m. |
| PDg | Predicate description generation | batch_69a99a4c3810819089d2dd0e23c8e46b |
completed | March 5, 2026, 2:59 p.m. |
Created at: March 4, 2026, 7:29 p.m.