Triple
T2512184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilhelm |
E52726
|
entity |
| Predicate | hasShortForm |
P43
|
FINISHED |
| Object | Willi |
E108645
|
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: Willi | Statement: [Wilhelm, hasShortForm, Willi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Willi Context triple: [Wilhelm, hasShortForm, Willi]
-
A.
Willi
chosen
Willi is a given name, typically a variant of Willy or William, used in various European countries.
-
B.
Wilbert
Wilbert is the given first name of American character actor Bill Cobbs, known for his numerous supporting roles in film and television.
-
C.
Willie
Willie is the first name of Willie Nelson, the iconic American country music singer-songwriter and cultural figure.
-
D.
Wido
Wido is a given name that functions as a variant form of the name Guido, used in various European languages.
-
E.
Melvin
Melvin is the full given name of legendary American voice actor and comedian Mel Blanc, famed for voicing many iconic Looney Tunes characters.
- 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_69ab4958e76481908a235377dd921c9e |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd1efb5c48190a9b47b39a388412b |
completed | March 7, 2026, 7:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af1faed61481909f13b8a014b39ed3 |
completed | March 9, 2026, 7:29 p.m. |
Created at: March 6, 2026, 9:46 p.m.