Triple
T21850314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coleen Rowley |
E539486
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Wesley Rowley
Wesley Rowley is known primarily as the husband of former FBI agent and whistleblower Coleen Rowley.
|
E1505466
|
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: Wesley Rowley | Statement: [Coleen Rowley, spouse, Wesley Rowley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wesley Rowley Context triple: [Coleen Rowley, spouse, Wesley Rowley]
-
A.
Wesley Dennis
Wesley Dennis was an American illustrator best known for his expressive drawings of horses in classic children's books.
-
B.
Wesley LaRue
Wesley LaRue is an individual notable enough to be recognized as a namesake of the surname LaRue.
-
C.
Wesley Saunders
Wesley Saunders is an American basketball player best known for starring as a versatile guard/forward for Harvard University, where he became one of the program’s top performers in the early 2010s.
-
D.
Wesley Michael Brown
Wesley Michael Brown is an English former professional footballer best known for his long tenure as a defender with Manchester United and the England national team.
-
E.
Wesley Taylor
Wesley Taylor is an American stage actor and singer best known for his work in Broadway musicals and television.
- 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: Wesley Rowley Triple: [Coleen Rowley, spouse, Wesley Rowley]
Generated description
Wesley Rowley is known primarily as the husband of former FBI agent and whistleblower Coleen Rowley.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wesley Rowley Target entity description: Wesley Rowley is known primarily as the husband of former FBI agent and whistleblower Coleen Rowley.
-
A.
Wesley Dennis
Wesley Dennis was an American illustrator best known for his expressive drawings of horses in classic children's books.
-
B.
Wesley LaRue
Wesley LaRue is an individual notable enough to be recognized as a namesake of the surname LaRue.
-
C.
Wesley Saunders
Wesley Saunders is an American basketball player best known for starring as a versatile guard/forward for Harvard University, where he became one of the program’s top performers in the early 2010s.
-
D.
Wesley Michael Brown
Wesley Michael Brown is an English former professional footballer best known for his long tenure as a defender with Manchester United and the England national team.
-
E.
Wesley Taylor
Wesley Taylor is an American stage actor and singer best known for his work in Broadway musicals and television.
- 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_69e0c476c3c88190a92d08ebb59a128a |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f0bd582ca48190890648fdee2a0c6e |
completed | April 28, 2026, 1:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a4bcfd92c8190a7f9f4a521c9086e |
completed | May 17, 2026, 11:14 p.m. |
| NEDg | Description generation | batch_6a0a4ccdd0a881908d32425b7cbb30c4 |
completed | May 17, 2026, 11:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a4de7d07c8190a0ccb1c229e7fc5d |
completed | May 17, 2026, 11:23 p.m. |
Created at: April 16, 2026, 6:56 p.m.