Triple
T14606404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MG Road, Bengaluru |
E342839
|
entity |
| Predicate | isBusiestTime |
P70162
|
FINISHED |
| Object | evenings |
—
|
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: evenings | Statement: [MG Road, Bengaluru, isBusiestTime, evenings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isBusiestTime Context triple: [MG Road, Bengaluru, isBusiestTime, evenings]
-
A.
isBusiestInSystem
Indicates that an entity has the highest level of activity or load compared to all other entities within the same system.
-
B.
isBusiestStationIn
Indicates that a station has the highest level of activity (e.g., passenger or traffic volume) within a specified area or system.
-
C.
isBusyDuring
Indicates that an entity is occupied or engaged with some activity throughout a specified time period.
-
D.
activityPeakPeriod
chosen
Indicates the time period during which an activity reaches its highest level or intensity.
-
E.
hasPeakHourService
Indicates that a service operates or is available during designated peak or high-demand hours.
- 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_69d822dec68081908c2553145c4051dc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb44bf67c8190b4c48a7715f9443e |
completed | April 14, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69de656f9f4c81909f815b6629a9ee39 |
completed | April 14, 2026, 4:03 p.m. |
Created at: April 10, 2026, 1:25 a.m.