Triple
T19453120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schilling |
E486665
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Anne Schilling
Anne Schilling is a mathematician known for her contributions to algebraic combinatorics and representation theory.
|
E1380102
|
NE FINISHED |
How this triple was built (4 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: Anne Schilling | Statement: [Schilling, hasNotableBearer, Anne Schilling]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anne Schilling Context triple: [Schilling, hasNotableBearer, Anne Schilling]
-
A.
Anne Schaefer
Anne Schaefer was an American silent film actress active in the early 20th century, appearing in numerous productions during the 1910s and 1920s.
-
B.
Victoria Schuck
Victoria Schuck was an American political scientist and educator known for her pioneering work on women in politics and her leadership roles in higher education.
-
C.
Lisa Brühlmann
Lisa Brühlmann is a Swiss film and television director and screenwriter known for her work on acclaimed series such as "The Girl Before" and "Killing Eve."
-
D.
Rachel Scheer
Rachel Scheer is an actress known for her role in the horror film "The Rage."
-
E.
Lisa Eilbacher
Lisa Eilbacher is an American actress best known for her roles in 1980s films and television series, including prominent appearances in action and drama movies.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Anne Schilling Triple: [Schilling, hasNotableBearer, Anne Schilling]
Generated description
Anne Schilling is a mathematician known for her contributions to algebraic combinatorics and representation theory.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Anne Schilling Target entity description: Anne Schilling is a mathematician known for her contributions to algebraic combinatorics and representation theory.
-
A.
Anne Schaefer
Anne Schaefer was an American silent film actress active in the early 20th century, appearing in numerous productions during the 1910s and 1920s.
-
B.
Victoria Schuck
Victoria Schuck was an American political scientist and educator known for her pioneering work on women in politics and her leadership roles in higher education.
-
C.
Lisa Brühlmann
Lisa Brühlmann is a Swiss film and television director and screenwriter known for her work on acclaimed series such as "The Girl Before" and "Killing Eve."
-
D.
Rachel Scheer
Rachel Scheer is an actress known for her role in the horror film "The Rage."
-
E.
Lisa Eilbacher
Lisa Eilbacher is an American actress best known for her roles in 1980s films and television series, including prominent appearances in action and drama movies.
- F. None of above. chosen
Provenance (5 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_69d8e8d86d608190bd199a98d0297f27 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6339407a08190a3e0213bfbb4df3d |
completed | April 20, 2026, 2:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07470ff794819098bb55f51cd32c4b |
completed | May 15, 2026, 4:17 p.m. |
| NEDg | Description generation | batch_6a0747f6b1d48190a3e70576ddb4feb2 |
completed | May 15, 2026, 4:21 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07492259488190a8c405598f9c8878 |
completed | May 15, 2026, 4:26 p.m. |
Created at: April 10, 2026, 1:38 p.m.