Triple
T21397223
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flowers |
E527816
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object |
Michael Hoste
Michael Hoste is an individual associated with the group or collective known as Flowers.
|
E1482692
|
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: Michael Hoste | Statement: [Flowers, hasMember, Michael Hoste]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Hoste Context triple: [Flowers, hasMember, Michael Hoste]
-
A.
Michael Pauw
Michael Pauw was a 17th-century Dutch merchant and director of the Dutch West India Company who was an early patroon and landowner in what is now New Jersey and New York.
-
B.
Philip Alan Hosterman
Philip Alan Hosterman was the father of American actress and singer Dove Cameron.
-
C.
Michael Pelmont
Michael Pelmont is a television producer best known for serving as an executive producer on the NBC sitcom "Lopez vs Lopez."
-
D.
Michael Fessier
Michael Fessier was an American screenwriter and author known for his work on Hollywood films in the 1930s and 1940s, often contributing to romantic comedies and musicals.
-
E.
Michel DeGraff
Michel DeGraff is a Haitian-born linguist known for his work on Haitian Creole, language and education, and linguistic theory as a professor at MIT.
- 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: Michael Hoste Triple: [Flowers, hasMember, Michael Hoste]
Generated description
Michael Hoste is an individual associated with the group or collective known as Flowers.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Michael Hoste Target entity description: Michael Hoste is an individual associated with the group or collective known as Flowers.
-
A.
Michael Pauw
Michael Pauw was a 17th-century Dutch merchant and director of the Dutch West India Company who was an early patroon and landowner in what is now New Jersey and New York.
-
B.
Philip Alan Hosterman
Philip Alan Hosterman was the father of American actress and singer Dove Cameron.
-
C.
Michael Pelmont
Michael Pelmont is a television producer best known for serving as an executive producer on the NBC sitcom "Lopez vs Lopez."
-
D.
Michael Fessier
Michael Fessier was an American screenwriter and author known for his work on Hollywood films in the 1930s and 1940s, often contributing to romantic comedies and musicals.
-
E.
Michel DeGraff
Michel DeGraff is a Haitian-born linguist known for his work on Haitian Creole, language and education, and linguistic theory as a professor at MIT.
- 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_69e0b51ff3748190935c0a513c62a12b |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8b11a2aec8190a60e53b90d0823b1 |
completed | April 22, 2026, 11:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a09bb4d8e34819084b8f3f172dd72e1 |
completed | May 17, 2026, 12:57 p.m. |
| NEDg | Description generation | batch_6a09bea3994481908b7a782fd384603a |
completed | May 17, 2026, 1:12 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a09bf9d2d508190a45847afa0d47337 |
completed | May 17, 2026, 1:16 p.m. |
Created at: April 16, 2026, 5:13 p.m.