Triple
T3817711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prague Metro |
E84295
|
entity |
| Predicate | peakFunction |
P52427
|
FINISHED |
| Object | high-capacity urban transport corridor |
—
|
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: high-capacity urban transport corridor | Statement: [Prague Metro, peakFunction, high-capacity urban transport corridor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: peakFunction Context triple: [Prague Metro, peakFunction, high-capacity urban transport corridor]
-
A.
peakType
Indicates the specific classification or category of a peak based on its form, prominence, or other defining characteristics.
-
B.
peakUse
Indicates the time, condition, or context in which something reaches its maximum level of use or intensity.
-
C.
peakStatus
Indicates the condition or phase of something at its highest or most intense point in its progression or lifecycle.
-
D.
peakService
Indicates that the service is operating during its highest-demand or peak usage period.
-
E.
peakRating
Indicates the highest rating value that has been achieved or recorded for an entity over a given period or context.
- 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_69aed931f5908190be2c07af66d4df25 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef188b474819087680db42b04ecdd |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee74a2bc081909b237df8b1e27653 |
completed | March 9, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69aef18748648190b85e62f7796ff4b4 |
completed | March 9, 2026, 4:12 p.m. |
Created at: March 9, 2026, 3:17 p.m.