Triple
T13058204
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Han |
E327631
|
entity |
| Predicate | relatedTitle |
P914
|
FINISHED |
| Object | Kagan |
E228617
|
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: Kagan | Statement: [Han, relatedTitle, Kagan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kagan Context triple: [Han, relatedTitle, Kagan]
-
A.
Kagan
chosen
Kagan is a surname most prominently associated with Elena Kagan, an Associate Justice of the United States Supreme Court.
-
B.
Kahn
Kahn is a surname most famously associated with Louis Kahn, the influential 20th-century architect known for his monumental and timeless modernist buildings.
-
C.
Kolb
Kolb is a surname most notably associated with American actor and comedian Clarence Kolb, known for his roles in early 20th-century film and vaudeville.
-
D.
Kahn-Ackermann
Kahn-Ackermann is a German surname most notably borne by the politician and diplomat Georg Kahn-Ackermann.
-
E.
Basalinsky
Basalinsky is the original family surname of British actor Alfie Bass, known for his work in mid-20th-century film, television, and theatre.
- 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_69d8076e64308190904fb5c93517c901 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d980be37208190962e91f1e19df159 |
completed | April 10, 2026, 10:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6cbe0bf3081909ff498ac66cb2aa6 |
completed | May 3, 2026, 4:15 a.m. |
Created at: April 9, 2026, 8:58 p.m.