Triple
T16468116
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kokane |
E399985
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Mr. Kane |
E369190
|
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. Kane | Statement: [Kokane, alsoKnownAs, Mr. Kane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mr. Kane Context triple: [Kokane, alsoKnownAs, Mr. Kane]
-
A.
Mr. Kane
chosen
Mr. Kane is a hip-hop artist who contributed a guest appearance to Snoop Dogg’s album "Paid tha Cost to Be da Boss."
-
B.
Mr. Kane
Mr. Kane is the husband of Mary Kane, a character associated with the backstory of Charles Foster Kane in the classic film "Citizen Kane."
-
C.
Lester Kane
Lester Kane is a wealthy, morally conflicted businessman who becomes the central love interest and tragic figure in Theodore Dreiser’s novel "Jennie Gerhardt."
-
D.
Marcus Kane
Marcus Kane is a central political leader and moral compass in the post-apocalyptic TV series "The 100," known for his evolution from strict authoritarian to compassionate advocate for peace.
-
E.
Louis Kane
Louis Kane is an American entrepreneur best known as a co-founder of the bakery-café chain Panera Bread.
- 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_69d87f2dac988190b74d6e185fa88ba4 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32dce342081909cad56dc92de13a2 |
completed | April 18, 2026, 7:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a004f5914dc81908c3b8cf999ee76a1 |
completed | May 10, 2026, 9:26 a.m. |
Created at: April 10, 2026, 5:11 a.m.