Triple
T18673414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clearlake Capital |
E456537
|
entity |
| Predicate | keyPerson |
P256
|
FINISHED |
| Object |
Chris Kruse
Chris Kruse is a senior executive and key investment professional at the private equity firm Clearlake Capital.
|
E1352184
|
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: Chris Kruse | Statement: [Clearlake Capital, keyPerson, Chris Kruse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chris Kruse Context triple: [Clearlake Capital, keyPerson, Chris Kruse]
-
A.
Brian Krause
Brian Krause is an American actor best known for playing the whitelighter Leo Wyatt on the television series "Charmed."
-
B.
Chris Weinke
Chris Weinke is a former American football quarterback best known for leading Florida State University to a national championship and winning the Heisman Trophy before playing in the NFL.
-
C.
Chris Sievernich
Chris Sievernich is a German film producer best known for his work on acclaimed art-house and independent films, including Wim Wenders’ "Paris, Texas."
-
D.
Josh Kramon
Josh Kramon is a television and film composer best known for scoring the cult mystery series "Veronica Mars."
-
E.
Michael Krueger
Michael Krueger is a notable individual distinguished enough to be recognized as a prominent bearer of the surname Krueger.
- 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: Chris Kruse Triple: [Clearlake Capital, keyPerson, Chris Kruse]
Generated description
Chris Kruse is a senior executive and key investment professional at the private equity firm Clearlake Capital.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Chris Kruse Target entity description: Chris Kruse is a senior executive and key investment professional at the private equity firm Clearlake Capital.
-
A.
Brian Krause
Brian Krause is an American actor best known for playing the whitelighter Leo Wyatt on the television series "Charmed."
-
B.
Chris Weinke
Chris Weinke is a former American football quarterback best known for leading Florida State University to a national championship and winning the Heisman Trophy before playing in the NFL.
-
C.
Chris Sievernich
Chris Sievernich is a German film producer best known for his work on acclaimed art-house and independent films, including Wim Wenders’ "Paris, Texas."
-
D.
Josh Kramon
Josh Kramon is a television and film composer best known for scoring the cult mystery series "Veronica Mars."
-
E.
Michael Krueger
Michael Krueger is a notable individual distinguished enough to be recognized as a prominent bearer of the surname Krueger.
- 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_69d8d38f72b4819090a935175d9ca8af |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e556b41cd881908f37bf7c85e96559 |
completed | April 19, 2026, 10:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a05ad226ff08190bf639fdf77ed0cf8 |
completed | May 14, 2026, 11:08 a.m. |
| NEDg | Description generation | batch_6a05aedf05c4819096ac6a61ada4b310 |
completed | May 14, 2026, 11:15 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a05afe523208190a97142cd8e3b887b |
completed | May 14, 2026, 11:20 a.m. |
Created at: April 10, 2026, 11:48 a.m.