Triple
T19954439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EYOF flame |
E479645
|
entity |
| Predicate | extinguishingMarks |
P137984
|
FINISHED |
| Object | official end of the European Youth Olympic Festival |
—
|
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: official end of the European Youth Olympic Festival | Statement: [EYOF flame, extinguishingMarks, official end of the European Youth Olympic Festival]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: extinguishingMarks Context triple: [EYOF flame, extinguishingMarks, official end of the European Youth Olympic Festival]
-
A.
extinguishes
Indicates that one entity causes another entity (such as a flame, light, or process) to cease, end, or be put out.
-
B.
extinguishedAt
Indicates that an extinguishing event occurred at a specific time or location associated with the subject.
-
C.
marksOn
Indicates that one entity bears visible signs, traces, or imprints that have been made or left by another entity.
-
D.
armorMarkings
Indicates that one entity bears specific markings, patterns, or insignia on its armor in relation to another entity or context.
-
E.
destroyedByFire
Indicates that something has been ruined, damaged, or rendered unusable as a direct result of a fire.
- 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_69e65aef16588190b3a40a3d49ef5080 |
completed | April 20, 2026, 4:57 p.m. |
| PD | Predicate disambiguation | batch_69e537f47c508190853c4e009c6b5566 |
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.