Triple
T14556250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rennes Metro |
E341548
|
entity |
| Predicate | offPeakServiceFrequency_minutes |
P114667
|
FINISHED |
| Object | about 4 to 8 |
—
|
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: about 4 to 8 | Statement: [Rennes Metro, offPeakServiceFrequency_minutes, about 4 to 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offPeakServiceFrequency_minutes Context triple: [Rennes Metro, offPeakServiceFrequency_minutes, about 4 to 8]
-
A.
offPeakServicePattern
Indicates the service pattern or schedule that applies during off-peak (non-rush-hour) times.
-
B.
peakHours
Indicates that an action, event, or condition occurs during the busiest or most heavily trafficked time period.
-
C.
typicalOffPeakServiceTo
Indicates the usual or standard off-peak (non-peak time) service pattern that operates to a given destination.
-
D.
typicalFrequencyWeekdayDaytime
Indicates the usual or most common frequency with which something occurs during daytime hours on weekdays.
-
E.
peakServicePeriod
Indicates the time interval during which a service experiences its highest or most intensive level of use or operation.
- 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_69d822db9c8481908213ceb39585f792 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb2f1490881908673f429e5288c86 |
completed | April 14, 2026, 9:34 p.m. |
| PD | Predicate disambiguation | batch_69de5c57489c8190b57917be1dba6ae6 |
completed | April 14, 2026, 3:25 p.m. |
| PDg | Predicate description generation | batch_69de5fb5ac548190932f238e37271741 |
completed | April 14, 2026, 3:39 p.m. |
Created at: April 10, 2026, 1:23 a.m.