Triple
T19971469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luxembourg at the Olympic Games |
E480084
|
entity |
| Predicate | hasSmallDelegations |
P138092
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Luxembourg at the Olympic Games, hasSmallDelegations, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSmallDelegations Context triple: [Luxembourg at the Olympic Games, hasSmallDelegations, true]
-
A.
hasDelegations
Indicates that an entity has assigned or transferred certain responsibilities, authority, or tasks to one or more other entities.
-
B.
numberOfDelegations
Indicates the total count of delegation instances associated with a given entity or context.
-
C.
smallestDelegationFrom
Indicates that the subject entity has the smallest (minimum-sized) delegation originating from the specified source entity, compared to all other delegations from that source.
-
D.
hasSpecialDelegatesPerProvince
Indicates that a given entity is associated with a specific number or set of special delegates allocated for each province.
-
E.
hasNumberOfDeputies
Indicates the specific count of deputies associated with or assigned to an entity.
- 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_69d8e523c19881909f9197037200dde6 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65bc9694881909a31841702ab9e5f |
completed | April 20, 2026, 5 p.m. |
| PD | Predicate disambiguation | batch_69e537f7e4848190b431a69ec3f1b609 |
completed | April 19, 2026, 8:15 p.m. |
| PDg | Predicate description generation | batch_69e543c42c688190a22f4d31ec692377 |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 10, 2026, 1:54 p.m.