Triple
T23511040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Schwartzman |
E572421
|
entity |
| Predicate | hasSurname |
P18
|
FINISHED |
| Object | Schwartzman |
—
|
NE NERFINISHED |
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: Schwartzman | Statement: [John Schwartzman, hasSurname, Schwartzman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schwartzman Context triple: [John Schwartzman, hasSurname, Schwartzman]
-
A.
Schwartzman
chosen
Schwartzman is a surname most notably associated with several American film industry figures, including cinematographer John Schwartzman and members of the Coppola family.
-
B.
dux Sagan
dux Sagan was a medieval ducal title associated with the Piast rulers of the Silesian town and region of Żagań.
-
C.
Max Wittmann
Max Wittmann is an individual notable enough to be recognized as a prominent bearer of the Wittmann surname.
-
D.
Santiago Ponzinibbio
Santiago Ponzinibbio is an Argentine professional mixed martial artist and longtime UFC welterweight contender known for his striking-heavy style and knockout power.
-
E.
Fernando Bautista
Fernando Bautista is a Filipino educator and entrepreneur best known for establishing the University of Baguio, a major private university in Baguio City, Philippines.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245b5e4208190bac8a6509867e394 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1aa7e99b081909620c4f951100023 |
completed | April 29, 2026, 6:51 a.m. |
Created at: April 17, 2026, 6:07 p.m.