Triple
T1493464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Trafford tram stop |
E29633
|
entity |
| Predicate | hasPeakTimeCrowding |
P18989
|
FINISHED |
| Object | on match days |
—
|
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: on match days | Statement: [Old Trafford tram stop, hasPeakTimeCrowding, on match days]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPeakTimeCrowding Context triple: [Old Trafford tram stop, hasPeakTimeCrowding, on match days]
-
A.
hasCrowdLevel
chosen
Indicates the degree or intensity of how crowded a place, event, or situation is.
-
B.
hasPeakHourService
Indicates that a service operates or is available during designated peak or high-demand hours.
-
C.
circulationPeak
Indicates the highest level or maximum point reached in the circulation of something (such as money, media, or resources) within a given period or system.
-
D.
isBusiestStationIn
Indicates that a station has the highest level of activity (e.g., passenger or traffic volume) within a specified area or system.
-
E.
peakDayAttendance
Indicates the number of attendees present on the single highest-attendance day within a given period or event.
- 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_69a498dba1d8819093b46a3a8d2485f1 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c6c665488190ae665f7a1b0563f5 |
completed | March 1, 2026, 11:07 p.m. |
| PD | Predicate disambiguation | batch_69a4c48902808190a8028d359bcf123e |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8:12 p.m.