Triple
T3554873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Clair station |
E75194
|
entity |
| Predicate | hasStreetcarLoop |
P50568
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [St. Clair station, hasStreetcarLoop, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStreetcarLoop Context triple: [St. Clair station, hasStreetcarLoop, yes]
-
A.
hasStreetcarSystem
Indicates that a place possesses or is served by an operational streetcar (tram) transit system.
-
B.
hasTramway
Indicates that a location or area is served by, contains, or is connected to a tramway system.
-
C.
hasBusLoop
Indicates that a location or facility includes a designated looped roadway or area specifically for bus circulation, stopping, or turning.
-
D.
hasRailroadTracksRunningThroughDowntown
Indicates that railroad tracks physically pass through and traverse the central downtown area of a place.
-
E.
hasLightRailSystem
Indicates that a place possesses and operates a light rail transit system.
- 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_69ad85d45090819086f34fb85d850a1e |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc05549d88190acdebdd542ea1a67 |
completed | March 8, 2026, 6:30 p.m. |
| PD | Predicate disambiguation | batch_69adb83270ac819083967db0570167d2 |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adba25c66c81909a05a97327828c41 |
completed | March 8, 2026, 6:04 p.m. |
Created at: March 8, 2026, 3:20 p.m.