Triple
T17255834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bill Spencer Jr. |
E418877
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Bill |
E17085
|
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: Bill | Statement: [Bill Spencer Jr., givenName, Bill]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bill Context triple: [Bill Spencer Jr., givenName, Bill]
-
A.
Bill
Bill is the generic name for the living, sentient bullet-like enemies that appear throughout the Mario video game series.
-
B.
Bill
Bill is a fictional character from the animated series "Vinnie & Bobby."
-
C.
Bill
chosen
Bill is a common masculine given name, typically used as a diminutive or nickname for William.
-
D.
Bill
Bill is a film featuring Mickey Rooney in a critically acclaimed dramatic role portraying a man with an intellectual disability.
-
E.
Bill
Bill is the ruthless leader of the Deadly Viper Assassination Squad and the central antagonist in Quentin Tarantino’s film "Kill Bill."
- 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_69d886d9ab108190b70edd8d17aa1204 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42e6ceb9c8190a4eeaf10e90cd5a0 |
completed | April 19, 2026, 1:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0170fd7f7c81908f417fa758e861a2 |
completed | May 11, 2026, 6:02 a.m. |
Created at: April 10, 2026, 5:39 a.m.