Triple
T15755054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FTSEMIB |
E381945
|
entity |
| Predicate | calculationHours |
P49248
|
FINISHED |
| Object | Borsa Italiana trading hours |
—
|
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: Borsa Italiana trading hours | Statement: [FTSEMIB, calculationHours, Borsa Italiana trading hours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: calculationHours Context triple: [FTSEMIB, calculationHours, Borsa Italiana trading hours]
-
A.
hoursPerDayDecimalTime
Indicates the number of hours per day expressed as a decimal value.
-
B.
calculationTime
chosen
Indicates the amount of time required to perform or complete a calculation.
-
C.
endTimeDetail
Indicates the specific or refined information about when an event, action, or state concludes.
-
D.
minutesPerHourDecimalTime
Indicates the number of minutes contained in one hour when using a decimal-based time system.
-
E.
timeEquivalentOf
Indicates that two temporal entities represent the same point in time or duration, possibly expressed in different formats or units.
- 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e05031f6a08190bfb333eced0a59a1 |
completed | April 16, 2026, 2:57 a.m. |
| PD | Predicate disambiguation | batch_69e00531e7ac8190a4190cce4f7fab4c |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:47 a.m.