Triple
T6431577
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Connie Schultz |
E129789
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Schultz |
E216222
|
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: Schultz | Statement: [Connie Schultz, familyName, Schultz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schultz Context triple: [Connie Schultz, familyName, Schultz]
-
A.
Schultz
chosen
Schultz is a surname of German origin borne by numerous notable individuals across fields such as entertainment, politics, and academia.
-
B.
Herr Schultz
Herr Schultz is a kindly, aging Jewish fruit-shop owner whose doomed romance with Fraulein Schneider provides a poignant emotional core to the musical *Cabaret*.
-
C.
Schafer
Schafer is a surname of German origin borne by various notable individuals across fields such as entertainment, sports, and academia.
-
D.
Menzel
Menzel is the surname of Idina Menzel, the American actress and singer best known for her roles in Broadway musicals and the film "Frozen."
-
E.
Stanley
Stanley is the given first name of Ann Dunham, the American anthropologist and mother of former U.S. President Barack Obama.
- 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_69c0084caac48190a7bc2ad8ba44536f |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0693cadf08190aca84888a3440b3d |
completed | March 22, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c640ec681881909c75a55b33c09eb6 |
completed | March 27, 2026, 8:33 a.m. |
Created at: March 22, 2026, 4:44 p.m.