Triple
T2229716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hong Kong Stock Exchange |
E48735
|
entity |
| Predicate | continuousTradingSession |
P2917
|
FINISHED |
| Object | 09:30–12:00 |
—
|
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: 09:30–12:00 | Statement: [Hong Kong Stock Exchange, continuousTradingSession, 09:30–12:00]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: continuousTradingSession Context triple: [Hong Kong Stock Exchange, continuousTradingSession, 09:30–12:00]
-
A.
hasTradingSession
Indicates that an entity participates in or is associated with a specific trading session or period during which trading activities occur.
-
B.
hasTradingHours
chosen
Indicates that an entity operates or is available for trading during specified time periods.
-
C.
hasAfterHoursSession
Indicates that an entity conducts or participates in a session that takes place outside of regular or standard operating hours.
-
D.
tradingHoursType
Indicates the classification of an entity’s trading hours, such as whether they are regular, extended, holiday-specific, or of another defined type.
-
E.
extendedIndefinitelyOn
Indicates that something was prolonged or continued without a specified end point in relation to something else.
- 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_69a88aa51b388190949868ec9766e587 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc069e0ac8190bcda8cba9f5c7a5d |
completed | March 7, 2026, 6:06 a.m. |
| PD | Predicate disambiguation | batch_69abbdadbb0c8190b3a1ede31b8acbfa |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.