Triple
T15611111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harold Schuster |
E375292
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Schuster |
E389423
|
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: Schuster | Statement: [Harold Schuster, familyName, Schuster]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schuster Context triple: [Harold Schuster, familyName, Schuster]
-
A.
Schuster
chosen
Schuster is a surname most notably associated with M. Lincoln Schuster, the American co-founder of the publishing company Simon & Schuster.
-
B.
Kutscher
Kutscher is a surname of German origin, often considered a variant spelling of Kutcher.
-
C.
Hufstedler
Hufstedler is the surname of Shirley Hufstedler, a prominent American judge and the first U.S. Secretary of Education.
-
D.
Schafer
Schafer is a surname of German origin borne by various notable individuals across fields such as entertainment, sports, and academia.
-
E.
Schultz
Schultz is a surname of German origin borne by numerous notable individuals across fields such as entertainment, politics, and academia.
- 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_69d85ccf2794819096cda4cbcb02d478 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e8148a0819087d6d69cc84487ca |
completed | April 16, 2026, 2:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff56d76c108190aa3cae2d7e17c301 |
completed | May 9, 2026, 3:46 p.m. |
Created at: April 10, 2026, 4:13 a.m.