Triple
T1491768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minnesota Lynx |
E29594
|
entity |
| Predicate | president |
P8
|
FINISHED |
| Object |
Carley Knox
Carley Knox is a sports executive best known for her leadership role in the WNBA’s Minnesota Lynx organization.
|
E241025
|
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: Carley Knox | Statement: [Minnesota Lynx, president, Carley Knox]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carley Knox Context triple: [Minnesota Lynx, president, Carley Knox]
-
A.
Lacey Pemberton
Lacey Pemberton is a popular high school girl and one of the central characters in John Green’s novel and film adaptation "Paper Towns."
-
B.
Callie Rivers
Callie Rivers is a former American professional volleyball player and the daughter of longtime NBA coach Doc Rivers.
-
C.
Brenna Harding
Brenna Harding is an Australian actress best known for her roles in the TV series "Puberty Blues" and the "Arkangel" episode of "Black Mirror."
-
D.
Kelly Grayson
Kelly Grayson is a central character on the science fiction comedy series "The Orville," serving as the ship's first officer and the ex-wife of Captain Ed Mercer.
-
E.
Tiana Rogers
Tiana Rogers was a Cherokee woman known for her marriage to Sam Houston, the American statesman and leader of the Republic of Texas.
- 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: Carley Knox Triple: [Minnesota Lynx, president, Carley Knox]
Generated description
Carley Knox is a sports executive best known for her leadership role in the WNBA’s Minnesota Lynx organization.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Carley Knox Target entity description: Carley Knox is a sports executive best known for her leadership role in the WNBA’s Minnesota Lynx organization.
-
A.
Lacey Pemberton
Lacey Pemberton is a popular high school girl and one of the central characters in John Green’s novel and film adaptation "Paper Towns."
-
B.
Callie Rivers
Callie Rivers is a former American professional volleyball player and the daughter of longtime NBA coach Doc Rivers.
-
C.
Brenna Harding
Brenna Harding is an Australian actress best known for her roles in the TV series "Puberty Blues" and the "Arkangel" episode of "Black Mirror."
-
D.
Kelly Grayson
Kelly Grayson is a central character on the science fiction comedy series "The Orville," serving as the ship's first officer and the ex-wife of Captain Ed Mercer.
-
E.
Tiana Rogers
Tiana Rogers was a Cherokee woman known for her marriage to Sam Houston, the American statesman and leader of the Republic of Texas.
- 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_69a498da82e08190ba833330d05f380f |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c6c3ace4819081bc2b86ee2486b6 |
completed | March 1, 2026, 11:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae5d78933c81908359b0010b9e6147 |
completed | March 9, 2026, 5:41 a.m. |
| NEDg | Description generation | batch_69ae5dd76d408190ab324280344c7b79 |
completed | March 9, 2026, 5:42 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae5e4bfda88190af66dcb564c1e731 |
completed | March 9, 2026, 5:44 a.m. |
Created at: March 1, 2026, 8:12 p.m.