Triple
T8921208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dalton |
E212418
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Richard Dalton
Richard Dalton is a personal name shared by multiple individuals across various fields, including sports, academia, and the arts.
|
E775906
|
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: Richard Dalton | Statement: [Dalton, hasNotableBearer, Richard Dalton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Richard Dalton Context triple: [Dalton, hasNotableBearer, Richard Dalton]
-
A.
Mel Daniels
Mel Daniels was an American professional basketball center best known as a dominant force in the ABA, where he won multiple MVP awards and championships with the Indiana Pacers.
-
B.
Al Burton
Al Burton was an American television producer and composer best known for his work on popular sitcoms such as "The Facts of Life."
-
C.
Don Simpson
Don Simpson was a prominent Hollywood film producer known for co-producing blockbuster action films such as "Top Gun," "Beverly Hills Cop," and "Bad Boys."
-
D.
Joseph Moran
Joseph Moran was the husband of acclaimed American character actress Thelma Ritter.
-
E.
Max Dennison
Max Dennison is the skeptical teenage protagonist of the Halloween-themed fantasy film "Hocus Pocus," whose actions accidentally resurrect three witches in Salem.
- 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: Richard Dalton Triple: [Dalton, hasNotableBearer, Richard Dalton]
Generated description
Richard Dalton is a personal name shared by multiple individuals across various fields, including sports, academia, and the arts.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Richard Dalton Target entity description: Richard Dalton is a personal name shared by multiple individuals across various fields, including sports, academia, and the arts.
-
A.
Mel Daniels
Mel Daniels was an American professional basketball center best known as a dominant force in the ABA, where he won multiple MVP awards and championships with the Indiana Pacers.
-
B.
Al Burton
Al Burton was an American television producer and composer best known for his work on popular sitcoms such as "The Facts of Life."
-
C.
Don Simpson
Don Simpson was a prominent Hollywood film producer known for co-producing blockbuster action films such as "Top Gun," "Beverly Hills Cop," and "Bad Boys."
-
D.
Joseph Moran
Joseph Moran was the husband of acclaimed American character actress Thelma Ritter.
-
E.
Max Dennison
Max Dennison is the skeptical teenage protagonist of the Halloween-themed fantasy film "Hocus Pocus," whose actions accidentally resurrect three witches in Salem.
- 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_69ca839481d48190b42b037e0d0f636c |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc665024f081909515e02e5f5b2221 |
completed | April 1, 2026, 12:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cffd8495488190a1d93f9e5b7e334d |
completed | April 3, 2026, 5:48 p.m. |
| NEDg | Description generation | batch_69d000d2c5688190b014ce33c04ff875 |
completed | April 3, 2026, 6:02 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d001a1056c819083793547dbd4b1ee |
completed | April 3, 2026, 6:06 p.m. |
Created at: March 30, 2026, 6:56 p.m.