Triple
T6052004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buster Moon |
E134815
|
entity |
| Predicate | friend |
P8712
|
FINISHED |
| Object | Gunter |
E563073
|
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: Gunter | Statement: [Buster Moon, friend, Gunter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gunter Context triple: [Buster Moon, friend, Gunter]
-
A.
Gunter
chosen
Gunter is a flamboyant, energetic pig who serves as one of the standout comedic performers in the animated musical film "Sing 2."
-
B.
Gunner
Gunner is a masculine given name and surname of English origin, often associated with strength and warrior-like qualities.
-
C.
Sperrle
Sperrle is a German surname most notably borne by Hugo Sperrle, a senior Luftwaffe field marshal during World War II.
-
D.
Gunta
Gunta is a given name most notably borne by Gunta Stölzl, a pioneering textile artist and the only female master at the Bauhaus school.
-
E.
Haynrode
Haynrode is a small village in the German state of Thuringia.
- 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_69c00877b6d4819096b0e163728b73a3 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c056f802988190aafdb7cbb087c828 |
completed | March 22, 2026, 8:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c11d077fe48190af9f896df9028800 |
completed | March 23, 2026, 10:59 a.m. |
Created at: March 22, 2026, 4:09 p.m.