Triple
T9206951
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charles Fleischer |
E221005
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Fleischer |
E179565
|
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: Fleischer | Statement: [Charles Fleischer, familyName, Fleischer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fleischer Context triple: [Charles Fleischer, familyName, Fleischer]
-
A.
Fleischer
chosen
Fleischer is a surname of German origin borne by various notable individuals across different fields.
-
B.
Fleisher
Fleisher is a surname most notably associated with Leon Fleisher, the acclaimed American pianist and conductor.
-
C.
Fleischer Studios
Fleischer Studios was a pioneering American animation studio best known for creating iconic characters like Betty Boop and animating early Popeye and Superman cartoons.
-
D.
Nat Fleischer
Nat Fleischer was an American boxing writer and historian best known as the founder and long-time editor of The Ring magazine.
-
E.
Florenz
Florenz was the first name of Florenz Ziegfeld Jr., the influential American Broadway impresario best known for creating the Ziegfeld Follies.
- 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_69ca83e9d0e081908bdb71097201a06c |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccd9b0b6788190908bee67a0c5d48f |
completed | April 1, 2026, 8:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d065e49fcc81909ddb838a8ad28c57 |
completed | April 4, 2026, 1:14 a.m. |
Created at: March 30, 2026, 7:26 p.m.