Triple
T14279336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Critérium du Dauphiné Libéré 1964 |
E354000
|
entity |
| Predicate | hasRelationToEvent |
P85529
|
FINISHED |
| Object | preparatory race for Tour de France |
—
|
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: preparatory race for Tour de France | Statement: [Critérium du Dauphiné Libéré 1964, hasRelationToEvent, preparatory race for Tour de France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRelationToEvent Context triple: [Critérium du Dauphiné Libéré 1964, hasRelationToEvent, preparatory race for Tour de France]
-
A.
isLinkedToEvent
Indicates that an entity has an association or connection with a specific event.
-
B.
relationshipToEvent
chosen
Indicates the specific way an entity is connected or related to a particular event.
-
C.
hasRelation
Indicates that there exists some specified relationship or association between two entities.
-
D.
hasCoSanctionedEventWith
Indicates that two or more entities have jointly imposed or participated in the same sanction-related event or action.
-
E.
refersToEventType
Indicates that one entity references or is associated with a specific type or category of event.
- 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_69d8278d25148190abf1a8c8f5f533ad |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6585270c8190a717127b2f5dab3b |
completed | April 14, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69de2a88446481909cd526da97a3b70f |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:10 a.m.