Triple
T3350168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liège–Bastogne–Liège 1966 |
E70471
|
entity |
| Predicate | distanceInKilometres |
P33049
|
FINISHED |
| Object | 253 |
—
|
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: 253 | Statement: [Liège–Bastogne–Liège 1966, distanceInKilometres, 253]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceInKilometres Context triple: [Liège–Bastogne–Liège 1966, distanceInKilometres, 253]
-
A.
approximateDistanceKm
Indicates the estimated distance between two entities measured in kilometers, typically with some degree of inaccuracy or approximation.
-
B.
range_km
Indicates the maximum distance, measured in kilometers, over which something can operate, travel, or be effective.
-
C.
lengthInKm
chosen
Indicates that one entity specifies the length or distance of another entity measured in kilometers.
-
D.
distance
Indicates the spatial separation or length between two points, objects, or locations.
-
E.
flightDistance
Indicates the measured distance covered by a flight between its origin and destination.
- 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_69ad85a4ef7c8190a29e2bbd6fa454e4 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb21f3ae48190a33530712da01bc3 |
completed | March 8, 2026, 5:30 p.m. |
| PD | Predicate disambiguation | batch_69ada42df1d48190874bb05f95deefde |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:12 p.m.