Triple
T12649847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MRT Purple Line |
E302126
|
entity |
| Predicate | peakHeadway_minutes |
P94711
|
FINISHED |
| Object | approximately 4 to 6 |
—
|
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: approximately 4 to 6 | Statement: [MRT Purple Line, peakHeadway_minutes, approximately 4 to 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: peakHeadway_minutes Context triple: [MRT Purple Line, peakHeadway_minutes, approximately 4 to 6]
-
A.
peakHeadway
chosen
Indicates the maximum time interval between consecutive service instances (e.g., vehicles or trips) during the busiest operating period.
-
B.
lengthInMinutes
Indicates the duration of something expressed as a number of minutes.
-
C.
peakUse
Indicates the time, condition, or context in which something reaches its maximum level of use or intensity.
-
D.
peakServicePeriod
Indicates the time interval during which a service experiences its highest or most intensive level of use or operation.
-
E.
spentTimeIn
Indicates that an entity has spent a certain amount or period of time in a particular place or context.
- 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_69d7bdec9f9c8190b4bac675b7588211 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961ae493481908f82e0d05dce20bd |
completed | April 10, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69d960b47130819097e1162ed4fc993a |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:18 p.m.