Triple
T4199643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eddy Merckx |
E86034
|
entity |
| Predicate | hourRecordDistanceKm |
P54317
|
FINISHED |
| Object | 49.431 |
—
|
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: 49.431 | Statement: [Eddy Merckx, hourRecordDistanceKm, 49.431]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hourRecordDistanceKm Context triple: [Eddy Merckx, hourRecordDistanceKm, 49.431]
-
A.
hourRecordDistance
Indicates that one entity holds or represents the record for the greatest distance covered within a one-hour time period relative to another entity or context.
-
B.
hasCyclingDistance
Indicates that there is a specified distance associated with traveling between entities by cycling.
-
C.
raceDistanceType
Indicates the specific type or category of distance over which a race is conducted.
-
D.
range_km
Indicates the maximum distance, measured in kilometers, over which something can operate, travel, or be effective.
-
E.
lengthInKm
Indicates that one entity specifies the length or distance of another entity measured in kilometers.
- 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_69aed93b89f48190a31f6d57c760e42f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af036243b4819097efe6b796823cd9 |
completed | March 9, 2026, 5:29 p.m. |
| PD | Predicate disambiguation | batch_69af01959c4881909eb1adcb3bdadbe6 |
completed | March 9, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69af02e4e2308190b527e3b78eb8fa71 |
completed | March 9, 2026, 5:27 p.m. |
Created at: March 9, 2026, 3:49 p.m.