Triple
T22663822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ma (2019 film) |
E559729
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object |
Dante Brown
Dante Brown is an American actor known for his roles in film and television, including a starring role in the 2019 psychological horror film "Ma."
|
E1548609
|
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: Dante Brown | Statement: [Ma (2019 film), stars, Dante Brown]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dante Brown Context triple: [Ma (2019 film), stars, Dante Brown]
-
A.
Dan Brown
Dan Brown is an American author best known for his fast-paced mystery thrillers that blend historical, religious, and conspiracy themes, including the bestselling novel "The Da Vinci Code."
-
B.
Dan Brown
Dan Brown is an Australian musician best known as a guitarist for the metalcore band The Amity Affliction.
-
C.
Dan Brownlie
Dan Brownlie is an English football manager best known for managing non-league side Basingstoke Town F.C.
-
D.
Thomas B. Harris
Thomas B. Harris was a local figure of historical significance after whom the village of Thomasboro, Illinois, was named.
-
E.
Theodore Winter
Theodore Winter is a high-ranking CIA officer and the main antagonist in the 2010 action thriller film "Salt."
- 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: Dante Brown Triple: [Ma (2019 film), stars, Dante Brown]
Generated description
Dante Brown is an American actor known for his roles in film and television, including a starring role in the 2019 psychological horror film "Ma."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dante Brown Target entity description: Dante Brown is an American actor known for his roles in film and television, including a starring role in the 2019 psychological horror film "Ma."
-
A.
Dan Brown
Dan Brown is an Australian musician best known as a guitarist for the metalcore band The Amity Affliction.
-
B.
Dan Brown
Dan Brown is an American author best known for his fast-paced mystery thrillers that blend historical, religious, and conspiracy themes, including the bestselling novel "The Da Vinci Code."
-
C.
Dan Brownlie
Dan Brownlie is an English football manager best known for managing non-league side Basingstoke Town F.C.
-
D.
Thomas B. Harris
Thomas B. Harris was a local figure of historical significance after whom the village of Thomasboro, Illinois, was named.
-
E.
Theodore Winter
Theodore Winter is a high-ranking CIA officer and the main antagonist in the 2010 action thriller film "Salt."
- 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_69e2454a158c819093b8e35f5045efb6 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f176617ed8819095a58a2c9f1e3918 |
completed | April 29, 2026, 3:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b73e409048190b435921e455d7bbd |
completed | May 18, 2026, 8:17 p.m. |
| NEDg | Description generation | batch_6a0b7541919c8190a5bb0f31560bf871 |
completed | May 18, 2026, 8:23 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b762f315c8190a85d804e26a6b1c5 |
completed | May 18, 2026, 8:27 p.m. |
Created at: April 17, 2026, 3:08 p.m.