Triple
T14743992
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lev Praha |
E346418
|
entity |
| Predicate | playedInternationalLeague |
P115603
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Lev Praha, playedInternationalLeague, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: playedInternationalLeague Context triple: [Lev Praha, playedInternationalLeague, yes]
-
A.
playedInternationally
Indicates that an individual has participated in official international-level events or competitions representing a country or equivalent national entity.
-
B.
interleaguePlayWith
Indicates a competitive sports relationship where teams from different leagues play against each other in official games.
-
C.
playsInternationalMatchesIn
Indicates that an athlete or team participates in international matches held in a specified location or competition context.
-
D.
playsInNationalAssociation
Indicates that an individual participates as a player in a specified national-level sports association or league.
-
E.
umpireLeague
Indicates that an umpire is associated with, works in, or officiates for a particular league.
- 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_69d822e6f1c88190bc494d491a907114 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7d002708190a32a4a45e96fc389 |
completed | April 14, 2026, 11:03 p.m. |
| PD | Predicate disambiguation | batch_69de8bf9331481909582045cd567d91f |
completed | April 14, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69de8f4b67cc8190b84b59fcec5cf579 |
completed | April 14, 2026, 7:02 p.m. |
Created at: April 10, 2026, 1:30 a.m.