Triple
T9213353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mads Nipper |
E221179
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Nipper |
E472904
|
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: Nipper | Statement: [Mads Nipper, familyName, Nipper]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nipper Context triple: [Mads Nipper, familyName, Nipper]
-
A.
Nipper
chosen
Nipper is the famous terrier dog depicted listening to a gramophone in the iconic "His Master’s Voice" trademark logo used by several major record companies.
-
B.
Prancer
Prancer is one of Santa Claus's legendary flying reindeer, traditionally depicted as helping pull his sleigh on Christmas Eve.
-
C.
Champ the Bulldog
Champ the Bulldog is the costumed canine mascot representing the University of Minnesota Duluth Bulldogs athletic teams.
-
D.
Piper the Dog
Piper the Dog is the costumed canine mascot representing Hamline University at its athletic events and campus activities.
-
E.
Hector the Bulldog
Hector the Bulldog is a tough, muscular bulldog character from the Looney Tunes cartoons, often portrayed as a protector of characters like Tweety.
- 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_69ca83eae42c8190a0ea9e040710a277 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccda05406081909893bec3a092d3ce |
completed | April 1, 2026, 8:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d06613daf88190a0128fd53ea1b134 |
completed | April 4, 2026, 1:15 a.m. |
Created at: March 30, 2026, 7:27 p.m.