Triple
T960391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norman Schwarzkopf Jr. |
E20722
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Schwarzkopf
Schwarzkopf is a German surname most prominently associated with U.S. Army General Norman Schwarzkopf Jr., who led coalition forces in the Gulf War.
|
E113450
|
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: Schwarzkopf | Statement: [Norman Schwarzkopf Jr., familyName, Schwarzkopf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schwarzkopf Context triple: [Norman Schwarzkopf Jr., familyName, Schwarzkopf]
-
A.
Redken
Redken is a professional haircare and hair color brand known for its salon-quality products and innovative, science-driven formulas.
-
B.
Revlon
Revlon is a major American cosmetics, skincare, fragrance, and personal care company known for its mass-market beauty products and global brand presence.
-
C.
Braun
Braun is a German surname most infamously associated with Eva Braun, the longtime companion and brief wife of Adolf Hitler.
-
D.
Kohl
Kohl is a German surname most prominently associated with Helmut Kohl, the long-serving Chancellor of Germany who oversaw the country’s reunification.
-
E.
Gillette
Gillette is a globally recognized American brand best known for its razors and shaving products.
- 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: Schwarzkopf Triple: [Norman Schwarzkopf Jr., familyName, Schwarzkopf]
Generated description
Schwarzkopf is a German surname most prominently associated with U.S. Army General Norman Schwarzkopf Jr., who led coalition forces in the Gulf War.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Schwarzkopf Target entity description: Schwarzkopf is a German surname most prominently associated with U.S. Army General Norman Schwarzkopf Jr., who led coalition forces in the Gulf War.
-
A.
Redken
Redken is a professional haircare and hair color brand known for its salon-quality products and innovative, science-driven formulas.
-
B.
Revlon
Revlon is a major American cosmetics, skincare, fragrance, and personal care company known for its mass-market beauty products and global brand presence.
-
C.
Braun
Braun is a German surname most infamously associated with Eva Braun, the longtime companion and brief wife of Adolf Hitler.
-
D.
Kohl
Kohl is a German surname most prominently associated with Helmut Kohl, the long-serving Chancellor of Germany who oversaw the country’s reunification.
-
E.
Gillette
Gillette is a globally recognized American brand best known for its razors and shaving products.
- 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_69a493b21f2881908132dcf45dcd2f36 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b412f9f48190be123e8c20f38962 |
completed | March 1, 2026, 9:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac11a3f8c481908f9ed37c44788cb7 |
completed | March 7, 2026, 11:53 a.m. |
| NEDg | Description generation | batch_69ac1339634c8190b83c39db30fc78b1 |
completed | March 7, 2026, 11:59 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac13931cf081908de84000f7b037fc |
completed | March 7, 2026, 12:01 p.m. |
Created at: March 1, 2026, 7:40 p.m.