Triple
T5745056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sheridan station (CTA Red Line) |
E126709
|
entity |
| Predicate | servesEventTraffic |
P29202
|
FINISHED |
| Object | Chicago Cubs games |
—
|
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: Chicago Cubs games | Statement: [Sheridan station (CTA Red Line), servesEventTraffic, Chicago Cubs games]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesEventTraffic Context triple: [Sheridan station (CTA Red Line), servesEventTraffic, Chicago Cubs games]
-
A.
servesEvent
Indicates that an entity provides, hosts, or facilitates a particular event for others.
-
B.
servesSeasonalTraffic
Indicates that an entity provides service only during specific seasons or periods of the year, rather than year-round.
-
C.
servesEventType
chosen
Indicates that an entity provides or supports a particular type or category of event.
-
D.
handlesSignificantShareOfTrafficAt
Indicates that an entity is responsible for managing or processing a substantial proportion of the traffic volume at a specified location or system.
-
E.
supportsTraffic
Indicates that one entity is capable of handling, carrying, or accommodating the flow or volume of traffic associated with another entity.
- 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_69c0083179548190b384b0bf3c08ca4d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02b52663c8190ab44258468d4296d |
completed | March 22, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69c021ca61688190875bd6107161c284 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:48 p.m.