Triple
T2187303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Graceland Cemetery |
E49179
|
entity |
| Predicate | hasNotableBurial |
P196
|
FINISHED |
| Object |
Oscar Mayer
Oscar Mayer was a German-American entrepreneur best known for founding the Oscar Mayer meat and cold cut company, a major U.S. food brand.
|
E242186
|
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: Oscar Mayer | Statement: [Graceland Cemetery, hasNotableBurial, Oscar Mayer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oscar Mayer Context triple: [Graceland Cemetery, hasNotableBurial, Oscar Mayer]
-
A.
Stouffer's
Stouffer's is a well-known American brand of frozen prepared meals and entrees owned by Nestlé.
-
B.
Heinz
Heinz is the German given name of Henry Alfred Kissinger, the influential American diplomat and former U.S. Secretary of State.
-
C.
Kraft
Kraft is a prominent American surname most widely associated with billionaire businessman and New England Patriots owner Robert Kraft.
-
D.
Snyder’s of Hanover
Snyder’s of Hanover is a popular American snack food company best known for its wide variety of pretzels and pretzel-based snacks.
-
E.
Reser’s Fine Foods
Reser’s Fine Foods is an American food company known for producing prepared salads, side dishes, and other refrigerated convenience foods for retail and foodservice markets.
- 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: Oscar Mayer Triple: [Graceland Cemetery, hasNotableBurial, Oscar Mayer]
Generated description
Oscar Mayer was a German-American entrepreneur best known for founding the Oscar Mayer meat and cold cut company, a major U.S. food brand.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Oscar Mayer Target entity description: Oscar Mayer was a German-American entrepreneur best known for founding the Oscar Mayer meat and cold cut company, a major U.S. food brand.
-
A.
Stouffer's
Stouffer's is a well-known American brand of frozen prepared meals and entrees owned by Nestlé.
-
B.
Heinz
Heinz is the German given name of Henry Alfred Kissinger, the influential American diplomat and former U.S. Secretary of State.
-
C.
Kraft
Kraft is a prominent American surname most widely associated with billionaire businessman and New England Patriots owner Robert Kraft.
-
D.
Snyder’s of Hanover
Snyder’s of Hanover is a popular American snack food company best known for its wide variety of pretzels and pretzel-based snacks.
-
E.
Reser’s Fine Foods
Reser’s Fine Foods is an American food company known for producing prepared salads, side dishes, and other refrigerated convenience foods for retail and foodservice markets.
- 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_69a88aa72d348190a9544bb5b8a4e71d |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbf130ef081908adb4a22f056be5b |
completed | March 7, 2026, 6 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae5dab44008190aeb4f77b73db2b36 |
completed | March 9, 2026, 5:42 a.m. |
| NEDg | Description generation | batch_69ae5e5fe37c8190bcf73200d32f5faa |
completed | March 9, 2026, 5:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae5ed1e3208190b46d5e8361c2a5f6 |
completed | March 9, 2026, 5:46 a.m. |
Created at: March 4, 2026, 7:45 p.m.