Triple
T1012705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AM General |
E21857
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object |
Kaiser Jeep
Kaiser Jeep was an American automobile manufacturer best known for producing civilian and military Jeep vehicles before its assets led to the formation of AM General.
|
E122504
|
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: Kaiser Jeep | Statement: [AM General, foundedBy, Kaiser Jeep]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kaiser Jeep Context triple: [AM General, foundedBy, Kaiser Jeep]
-
A.
Jeep
Jeep is an American automotive marque best known for its rugged sport utility vehicles and off-road capable 4x4s.
-
B.
DeSoto
DeSoto is a suburban city in the Dallas–Fort Worth metropolitan area in North Texas.
-
C.
AM General
AM General is an American heavy vehicle manufacturer best known for developing the military Humvee and its civilian counterpart, the Hummer.
-
D.
Durant Motors
Durant Motors was an early 20th-century American automobile manufacturer created by General Motors co-founder William C. Durant after his departure from GM.
-
E.
Niva
Niva was a prominent Russian literary and illustrated weekly magazine of the late 19th and early 20th centuries, known for publishing fiction, poetry, and cultural commentary.
- 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: Kaiser Jeep Triple: [AM General, foundedBy, Kaiser Jeep]
Generated description
Kaiser Jeep was an American automobile manufacturer best known for producing civilian and military Jeep vehicles before its assets led to the formation of AM General.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kaiser Jeep Target entity description: Kaiser Jeep was an American automobile manufacturer best known for producing civilian and military Jeep vehicles before its assets led to the formation of AM General.
-
A.
Jeep
Jeep is an American automotive marque best known for its rugged sport utility vehicles and off-road capable 4x4s.
-
B.
DeSoto
DeSoto is a suburban city in the Dallas–Fort Worth metropolitan area in North Texas.
-
C.
AM General
AM General is an American heavy vehicle manufacturer best known for developing the military Humvee and its civilian counterpart, the Hummer.
-
D.
Durant Motors
Durant Motors was an early 20th-century American automobile manufacturer created by General Motors co-founder William C. Durant after his departure from GM.
-
E.
Niva
Niva was a prominent Russian literary and illustrated weekly magazine of the late 19th and early 20th centuries, known for publishing fiction, poetry, and cultural commentary.
- 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_69a493c68e24819080ed0ee8bcfd5ce0 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b7a8b254819089ffed9cb62a6930 |
completed | March 1, 2026, 10:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac3bad654c81909dd59211fafa8b2c |
completed | March 7, 2026, 2:52 p.m. |
| NEDg | Description generation | batch_69ac3c41ab70819090084c508dbfd295 |
completed | March 7, 2026, 2:54 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac3cbb30d081909759df25c21eb275 |
completed | March 7, 2026, 2:56 p.m. |
Created at: March 1, 2026, 7:41 p.m.