Triple
T5713431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Partners (2014 album) |
E125964
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Jay Landers
Jay Landers is an American record producer and A&R executive best known for his extensive work with major artists such as Barbra Streisand and Josh Groban.
|
E540159
|
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: Jay Landers | Statement: [Partners (2014 album), producer, Jay Landers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jay Landers Context triple: [Partners (2014 album), producer, Jay Landers]
-
A.
Danny B. Landres
Danny B. Landres was an American film editor and director known for his work on mid-20th-century science fiction and genre films.
-
B.
Michael Lander
Michael Lander is the disturbed Vietnam War veteran and blimp pilot who orchestrates a terrorist attack in Thomas Harris’s thriller novel "Black Sunday."
-
C.
Bob Landers
Bob Landers is a fictional character from the American television sitcom "The Debbie Reynolds Show."
-
D.
Jeremy Kemp
Jeremy Kemp was a British character actor known for his roles in films such as "The Blue Max," "A Bridge Too Far," and numerous television dramas.
-
E.
Mark Okerstrom
Mark Okerstrom is a Canadian business executive best known for serving as the former CEO of Expedia Group.
- 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: Jay Landers Triple: [Partners (2014 album), producer, Jay Landers]
Generated description
Jay Landers is an American record producer and A&R executive best known for his extensive work with major artists such as Barbra Streisand and Josh Groban.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jay Landers Target entity description: Jay Landers is an American record producer and A&R executive best known for his extensive work with major artists such as Barbra Streisand and Josh Groban.
-
A.
Danny B. Landres
Danny B. Landres was an American film editor and director known for his work on mid-20th-century science fiction and genre films.
-
B.
Michael Lander
Michael Lander is the disturbed Vietnam War veteran and blimp pilot who orchestrates a terrorist attack in Thomas Harris’s thriller novel "Black Sunday."
-
C.
Bob Landers
Bob Landers is a fictional character from the American television sitcom "The Debbie Reynolds Show."
-
D.
Jeremy Kemp
Jeremy Kemp was a British character actor known for his roles in films such as "The Blue Max," "A Bridge Too Far," and numerous television dramas.
-
E.
Mark Okerstrom
Mark Okerstrom is a Canadian business executive best known for serving as the former CEO of Expedia Group.
- 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_69c0082d6fe48190b777fb383769e5c8 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c024b5205c8190aaab291a6e485ec1 |
completed | March 22, 2026, 5:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c05a74b350819099d8881ef248e1e7 |
completed | March 22, 2026, 9:09 p.m. |
| NEDg | Description generation | batch_69c05cfae55c81908658b4b5d5f03c96 |
completed | March 22, 2026, 9:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c05e0720988190bce708c165d861c9 |
completed | March 22, 2026, 9:24 p.m. |
Created at: March 22, 2026, 3:46 p.m.