Triple
T7426883
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UEFA Champions League 2008–09 |
E171390
|
entity |
| Predicate | numberOfAssociationsRepresented |
P76934
|
FINISHED |
| Object | 18 |
—
|
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: 18 | Statement: [UEFA Champions League 2008–09, numberOfAssociationsRepresented, 18]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfAssociationsRepresented Context triple: [UEFA Champions League 2008–09, numberOfAssociationsRepresented, 18]
-
A.
numberOfAssociateMembers
Indicates the total count of associate members linked to a given entity.
-
B.
participatingAssociations
Indicates that certain associations are involved as participants in a given activity, event, or relationship.
-
C.
hasNumberOfLiaisons
Indicates the quantity of liaison roles, connections, or intermediary relationships associated with a given entity.
-
D.
representsInRelationsWith
Indicates that an entity serves as a representative or proxy for another entity within a specified relationship or set of relationships.
-
E.
numberOfNGOsRepresented
Indicates the count of distinct non-governmental organizations that are represented in a given context or 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_69c68a63491881909281f73d4d5643bf |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f3055b7881908269ab909c5a85b5 |
completed | March 27, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69c6f03648d08190b862d07fef71210c |
completed | March 27, 2026, 9:01 p.m. |
| PDg | Predicate description generation | batch_69c6f1ee5ab8819091082324f2dc3b8c |
completed | March 27, 2026, 9:09 p.m. |
Created at: March 27, 2026, 3:12 p.m.