Triple
T10468431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Wonderful |
E246862
|
entity |
| Predicate | hasTitle |
P38
|
FINISHED |
| Object | Mr. Wonderful |
E246862
|
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: Mr. Wonderful | Statement: [Mr. Wonderful, hasTitle, Mr. Wonderful]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mr. Wonderful Context triple: [Mr. Wonderful, hasTitle, Mr. Wonderful]
-
A.
Mr. Wonderful
chosen
Mr. Wonderful is a 1993 romantic comedy film about a New York electrician who schemes to find a new husband for his ex-wife so he can afford his dream business.
-
B.
Mr. Right
Mr. Right is a 2015 action-romantic comedy film in which Sam Rockwell plays a eccentric hitman who falls in love while being pursued by his former employers.
-
C.
Mr. Jones
"Mr. Jones" is a hit alternative rock song by Counting Crows, known for its introspective lyrics about fame, dreams, and identity.
-
D.
Miss O'Dell
"Miss O'Dell" is a 1973 George Harrison song, released as the B-side to "Give Me Love (Give Me Peace on Earth)" and inspired by his friend and Apple Records secretary Chris O'Dell.
-
E.
Mr. Sparks
Mr. Sparks is a friendly, mechanically skilled character in the Noddy children's stories who often helps fix things in Toyland.
- 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_69d381c16c248190a2fe5b471e584e9c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5092ef810819093a4d1df83aeac09 |
completed | April 7, 2026, 1:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d89ff1cd948190a1ef331fb810bf26 |
completed | April 10, 2026, 7 a.m. |
Created at: April 6, 2026, 12:20 p.m.