Triple
T3947948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris Half Marathon |
E84791
|
entity |
| Predicate | courseLocation |
P16025
|
FINISHED |
| Object | streets of Paris |
—
|
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: streets of Paris | Statement: [Paris Half Marathon, courseLocation, streets of Paris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: courseLocation Context triple: [Paris Half Marathon, courseLocation, streets of Paris]
-
A.
trainingFacilityLocation
Indicates the place or site where a training facility is situated or operates.
-
B.
courseEndPoint
Indicates the final location or destination at which a course, route, or path terminates.
-
C.
courseSetting
chosen
Indicates the context or environment in which a course is delivered or conducted.
-
D.
courseDirection
Indicates the orientation or path that something follows or is intended to follow, such as the direction of movement, flow, or progression.
-
E.
trainingLocationType
Indicates the type or category of place where a training activity occurs.
- 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_69aed934fbfc8190847068e4546de963 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefaa5afdc8190b709af2473d75d02 |
completed | March 9, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69aef8ed04e4819096bced8971cd888d |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:30 p.m.