Triple
T10101896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schultz |
E216222
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Shultz |
E755703
|
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: Shultz | Statement: [Schultz, hasVariant, Shultz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shultz Context triple: [Schultz, hasVariant, Shultz]
-
A.
Shultz
chosen
Shultz is a surname most prominently associated with George P. Shultz, a key American economist, diplomat, and former U.S. Secretary of State.
-
B.
Henry Shultz
Henry Shultz was a 19th-century entrepreneur and bridge builder best known for establishing the town of Hamburg, South Carolina, as a commercial rival to nearby Augusta, Georgia.
-
C.
Frank Gresham
Frank Gresham is a central character in Anthony Trollope’s novel "Doctor Thorne," portrayed as a young English gentleman torn between love and the financial pressures of his aristocratic family.
-
D.
Newt Geiszler
Newt Geiszler is a quirky, hyper-intelligent kaiju-obsessed scientist and former PPDC researcher in the Pacific Rim film series.
-
E.
Michael Schultz
Michael Schultz is an American film and television director best known for his influential work on 1970s comedies and dramas, including the cult classic "Car Wash."
- 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_69ca83d039f08190b9d10363221c69fb |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cdd099c21c819097aac4f0f168a2da |
completed | April 2, 2026, 2:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2b6d3efec8190b1432ca614aeb334 |
completed | April 5, 2026, 7:24 p.m. |
Created at: March 30, 2026, 9:02 p.m.