Triple
T3768615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schneider Electric Marathon de Paris |
E82740
|
entity |
| Predicate | approximateFinishersPerYear |
P27342
|
FINISHED |
| Object | over 40,000 |
—
|
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: over 40,000 | Statement: [Schneider Electric Marathon de Paris, approximateFinishersPerYear, over 40,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateFinishersPerYear Context triple: [Schneider Electric Marathon de Paris, approximateFinishersPerYear, over 40,000]
-
A.
qualificationEndYear
Indicates the calendar year in which a qualification, certification, or course of study was completed or ended.
-
B.
approximateYearOfCompletion
Indicates the estimated calendar year in which something was completed, rather than an exact or confirmed year.
-
C.
typicalNumberOfAthletes
chosen
Indicates the usual or average number of athletes associated with or participating in a given context, event, or entity.
-
D.
serializationEndYear
Indicates the year in which the serialization or serialized publication of an entity concluded.
-
E.
approximateStartYear
Indicates that the associated year value represents an estimated or imprecise starting year for an event, state, or relationship rather than an exact one.
- 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_69ad8b207b0081909d2b48843fbd8795 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcc2d4b848190bf63fb3ed5d3b2d9 |
completed | March 8, 2026, 7:21 p.m. |
| PD | Predicate disambiguation | batch_69adc04ec36c8190bd5b944d4f4d32aa |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:35 p.m.