Triple
T1887097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jaromír Jágr |
E39986
|
entity |
| Predicate | reasonForJerseyNumber |
P33050
|
FINISHED |
| Object | to commemorate the 1968 Warsaw Pact invasion of Czechoslovakia |
—
|
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: to commemorate the 1968 Warsaw Pact invasion of Czechoslovakia | Statement: [Jaromír Jágr, reasonForJerseyNumber, to commemorate the 1968 Warsaw Pact invasion of Czechoslovakia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForJerseyNumber Context triple: [Jaromír Jágr, reasonForJerseyNumber, to commemorate the 1968 Warsaw Pact invasion of Czechoslovakia]
-
A.
jerseyNumber
Indicates the specific uniform number assigned to and worn by an individual, typically in a sports context.
-
B.
leaderJerseyColor
Indicates the color of the jersey worn by the current leader in a competition or ranking.
-
C.
wearsJerseyFor
Indicates that one entity wears a jersey representing, belonging to, or in support of another entity (such as a team, organization, or individual).
-
D.
leaderJerseyName
Indicates the name of the jersey worn by the current leader in a competition or ranking.
-
E.
reasonForName
Indicates the explanation or cause behind why an entity has a particular name.
- 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_69a88633e4fc8190b7eb40463e048ec5 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb121a3cc81909c60ac65627142d1 |
completed | March 7, 2026, 5:01 a.m. |
| PD | Predicate disambiguation | batch_69abafe61bc48190ac9ead027df930e1 |
completed | March 7, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69abb11bfd2c8190a805372589f73238 |
completed | March 7, 2026, 5:01 a.m. |
Created at: March 4, 2026, 7:34 p.m.