Triple
T6614636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spanish football league system |
E149317
|
entity |
| Predicate | topDivisionNumberOfClubs |
P26952
|
FINISHED |
| Object | 20 |
—
|
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: 20 | Statement: [Spanish football league system, topDivisionNumberOfClubs, 20]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: topDivisionNumberOfClubs Context triple: [Spanish football league system, topDivisionNumberOfClubs, 20]
-
A.
topDivision
Indicates that an entity belongs to the highest-level division or tier within a hierarchical structure.
-
B.
typicalNumberOfTopDivisionTeams
chosen
Indicates the usual or standard number of teams that compete in the highest-level division of a league or competition.
-
C.
numberOfDivisionsInConference
Indicates the total count of divisions that exist within a given conference.
-
D.
topDivisionOf
Indicates that one administrative or organizational unit is the highest-level division within the structure of another entity.
-
E.
topLevelDivisionCount
Indicates the number of primary administrative or organizational divisions directly under a given entity.
- 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_69c687ebc680819094caf71faba2efe2 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6bdb88cc881908f35648c15a7dc85 |
completed | March 27, 2026, 5:26 p.m. |
| PD | Predicate disambiguation | batch_69c6ad007c1c8190af425f51011c7ad1 |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:57 p.m.