Triple
T840233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jackson |
E18159
|
entity |
| Predicate | hasCognate |
P2525
|
FINISHED |
| Object |
Jensen
Jensen is a Scandinavian-origin surname and given name, most commonly associated with Danish and Norwegian patronymic naming traditions.
|
E100649
|
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: Jensen | Statement: [Jackson, hasCognate, Jensen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jensen Context triple: [Jackson, hasCognate, Jensen]
-
A.
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.
-
B.
Maxus
Maxus is a commercial vehicle brand known for producing vans, pickups, and light trucks, owned by the Chinese automotive giant SAIC Motor.
-
C.
IM Motors
IM Motors is a Chinese premium electric vehicle brand known for its smart, tech-focused cars developed under SAIC Motor.
-
D.
Mercury Milan
The Mercury Milan is a mid-size sedan produced by Ford's Mercury division from 2006 to 2011, positioned as a more upscale counterpart to the Ford Fusion.
-
E.
Bilen
Bilen is a Cushitic language spoken primarily by the Bilen people in central Eritrea.
- 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: Jensen Triple: [Jackson, hasCognate, Jensen]
Generated description
Jensen is a Scandinavian-origin surname and given name, most commonly associated with Danish and Norwegian patronymic naming traditions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jensen Target entity description: Jensen is a Scandinavian-origin surname and given name, most commonly associated with Danish and Norwegian patronymic naming traditions.
-
A.
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.
-
B.
Maxus
Maxus is a commercial vehicle brand known for producing vans, pickups, and light trucks, owned by the Chinese automotive giant SAIC Motor.
-
C.
IM Motors
IM Motors is a Chinese premium electric vehicle brand known for its smart, tech-focused cars developed under SAIC Motor.
-
D.
Mercury Milan
The Mercury Milan is a mid-size sedan produced by Ford's Mercury division from 2006 to 2011, positioned as a more upscale counterpart to the Ford Fusion.
-
E.
Bilen
Bilen is a Cushitic language spoken primarily by the Bilen people in central Eritrea.
- 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_69a49389f44881909a608fb27d89f247 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4abe5d7848190b15e0cb343b6f4ba |
completed | March 1, 2026, 9:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7929860f081909c86f84d7cfe6acb |
completed | March 4, 2026, 2:02 a.m. |
| NEDg | Description generation | batch_69a796370f388190b23cd19cc3fa5a3b |
completed | March 4, 2026, 2:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a796bee5388190ab0abf0bfa08ad97 |
completed | March 4, 2026, 2:19 a.m. |
Created at: March 1, 2026, 7:38 p.m.