Triple
T8616209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilbert Robinson |
E204043
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Wilbert |
E167389
|
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: Wilbert | Statement: [Wilbert Robinson, givenName, Wilbert]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wilbert Context triple: [Wilbert Robinson, givenName, Wilbert]
-
A.
Wilbert
chosen
Wilbert is the given first name of American character actor Bill Cobbs, known for his numerous supporting roles in film and television.
-
B.
Willi
Willi is a given name, typically a variant of Willy or William, used in various European countries.
-
C.
Melvin
Melvin is the given first name of Mel Lastman, a prominent Canadian businessman and former longtime mayor of Toronto.
-
D.
Melvin
Melvin is the full given name of legendary American voice actor and comedian Mel Blanc, famed for voicing many iconic Looney Tunes characters.
-
E.
Melvin
Melvin is a masculine given name of English origin commonly used in various English-speaking countries.
- 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_69ca832ceab8819096e4a9f546695079 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cc4703b57c81909511de72fa5c38d7 |
completed | March 31, 2026, 10:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cea923ae148190a973ef8ad6ccac9a |
completed | April 2, 2026, 5:36 p.m. |
Created at: March 30, 2026, 6:25 p.m.