Triple
T334248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Willem |
E6688
|
entity |
| Predicate | hasShortForm |
P43
|
FINISHED |
| Object | Willy |
E17731
|
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: Willy | Statement: [Willem, hasShortForm, Willy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Willy Context triple: [Willem, hasShortForm, Willy]
-
A.
Willy
chosen
Willy is a common diminutive form of the given name William, often used as an informal or affectionate nickname.
-
B.
Earl
An Earl is a noble rank in the British and some European peerage systems, historically positioned below a marquess and above a viscount.
-
C.
Herman
Herman is a surname most notably associated with Edward S. Herman, an American economist, media analyst, and critic of U.S. foreign policy.
-
D.
Herman
Herman is the given name of Belgian politician Herman De Croo, a long-serving liberal statesman and former President of the Belgian Chamber of Representatives.
-
E.
Frank Darling
Frank Darling was a prominent Canadian architect of the late 19th and early 20th centuries, known for designing many significant institutional and commercial buildings in Toronto.
- 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_69a2e79434908190a9d5afe415153ad9 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eac641708190b85fa21368e5de8e |
completed | Feb. 28, 2026, 1:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4034a3e248190853d58b4f27d1d74 |
completed | March 1, 2026, 9:13 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.