Triple
T12963510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aba Main Market |
E321205
|
entity |
| Predicate | typicalTradingDays |
P2916
|
FINISHED |
| Object | Monday |
—
|
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: Monday | Statement: [Aba Main Market, typicalTradingDays, Monday]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalTradingDays Context triple: [Aba Main Market, typicalTradingDays, Monday]
-
A.
hasTradingDays
chosen
Indicates that an entity is associated with specific days on which trading or commercial transactions are conducted.
-
B.
typicalDates
Indicates the usual or standard dates during which something typically occurs, is valid, or is scheduled.
-
C.
isBusinessDayIn
Indicates that a given date falls on a recognized working day (non-weekend, non-holiday) within a specified calendar, region, or jurisdiction.
-
D.
typicalEventDay
Indicates the day on which an event is normally or most commonly held or occurs.
-
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.
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_69d80763bd6c819094437da5b20b01d2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e59a4c88190907d05b8d57dae89 |
completed | April 10, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69d97dba57988190b786ffed55687a72 |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 8:25 p.m.