Triple
T23233346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Europe/Madrid |
E581219
|
entity |
| Predicate | typicalBusinessHoursReference |
P10068
|
FINISHED |
| Object | Madrid local time |
—
|
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: Madrid local time | Statement: [Europe/Madrid, typicalBusinessHoursReference, Madrid local time]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalBusinessHoursReference Context triple: [Europe/Madrid, typicalBusinessHoursReference, Madrid local time]
-
A.
typicalBusinessHourStartLocalTime
Indicates the local time at which a business’s normal operating hours typically begin.
-
B.
usedInBusinessHours
Indicates that something is utilized or occurs during designated business operating hours.
-
C.
hoursOfOperation
chosen
Indicates the time periods during which a place or service is open and available for use.
-
D.
typicalTradingHoursLocalTime
Indicates the usual daily time range during which trading activity occurs, expressed in the local time of the relevant market or venue.
-
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_69e2460556f88190be1744a84a84173f |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f192e70b2c8190abede6e3cd9344f7 |
completed | April 29, 2026, 5:11 a.m. |
| PD | Predicate disambiguation | batch_69effcdadec0819092ec1749ee453b4e |
completed | April 28, 2026, 12:18 a.m. |
Created at: April 17, 2026, 4:09 p.m.