Triple
T14167258
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Willy Borchers |
E351110
|
entity |
| Predicate | givenName |
P17
|
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: [Willy Borchers, givenName, Willy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Willy Context triple: [Willy Borchers, givenName, Willy]
-
A.
Willy
chosen
Willy is a common diminutive form of the given name William, often used as an informal or affectionate nickname.
-
B.
Willie
Willie is the first name of Willie Nelson, the iconic American country music singer-songwriter and cultural figure.
-
C.
Willie
Willie is a character from the classic American television sitcom "Happy Days," which nostalgically portrays life in the 1950s and 1960s.
-
D.
Willie
Willie is the given name of Willie Blount, an American politician who served as governor of Tennessee in the early 19th century.
-
E.
Willie
Willie is a masculine given name commonly used in English-speaking countries, often as a diminutive of William.
- 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_69d8278775fc8190b0802d22ca2f495d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61b355f08190864c7322bbcb766d |
completed | April 14, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcf7f57ad88190aeb8ee0f834bfa20 |
completed | May 7, 2026, 8:37 p.m. |
Created at: April 10, 2026, 1 a.m.