Triple
T9266970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Olympic Games mascots |
E222724
|
entity |
| Predicate | notableExample |
P1503
|
FINISHED |
| Object | Waldi |
E52542
|
NE 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: Waldi | Statement: [Olympic Games mascots, notableExample, Waldi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Waldi Context triple: [Olympic Games mascots, notableExample, Waldi]
-
A.
Waldi
chosen
Waldi is the dachshund dog character that served as the first official Olympic mascot, created for the 1972 Summer Games in Munich.
-
B.
Erwin Bootz
Erwin Bootz was a German pianist best known as a member of the renowned vocal ensemble the Comedian Harmonists.
-
C.
Werneck
Werneck is a market town in the Schweinfurt district of northern Bavaria, Germany, known for its baroque palace and surrounding rural landscape.
-
D.
Rudi Fehr
Rudi Fehr was a German-born American film editor known for his work on numerous Hollywood films from the 1940s through the 1970s.
-
E.
Willi Graf
Willi Graf was a German medical student and devout Catholic who became a key member of the White Rose resistance group, opposing the Nazi regime and ultimately being executed for his involvement.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca841f2e808190a64f4c31903a1332 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd074bac9481909419988a9e8d9bd5 |
completed | April 1, 2026, 11:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d09c193b548190afe79d0c84fa2bd3 |
completed | April 4, 2026, 5:05 a.m. |
Created at: March 30, 2026, 7:33 p.m.