Triple
T7785505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shanté Smith |
E187231
|
entity |
| Predicate | createdBy |
P806
|
FINISHED |
| Object |
Mark Brown
Mark Brown is a creator known for his work associated with American rapper and actress Shanté Smith, better known as Da Brat.
|
E692731
|
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: Mark Brown | Statement: [Shanté Smith, createdBy, Mark Brown]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mark Brown Context triple: [Shanté Smith, createdBy, Mark Brown]
-
A.
Mark Brown
Mark Brown is an American filmmaker and screenwriter best known for writing and directing the romantic comedy film "Two Can Play That Game."
-
B.
Matt Brown
Matt Brown is an American mixed martial artist and longtime UFC welterweight known for his aggressive, brawling style and high finishing rate.
-
C.
Greg Brown
Greg Brown is an American ice hockey coach and former defenseman best known for leading the Boston College Eagles men's hockey program.
-
D.
Jonathan Brown
Jonathan Brown is a cinematographer best known for his work on major studio comedies and mainstream Hollywood films, including the 2006 reboot of The Pink Panther.
-
E.
Rob Brown
Rob Brown is an American actor best known for his film debut in "Finding Forrester" and his role as a high school basketball player in "Coach Carter."
- 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: Mark Brown Triple: [Shanté Smith, createdBy, Mark Brown]
Generated description
Mark Brown is a creator known for his work associated with American rapper and actress Shanté Smith, better known as Da Brat.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mark Brown Target entity description: Mark Brown is a creator known for his work associated with American rapper and actress Shanté Smith, better known as Da Brat.
-
A.
Mark Brown
Mark Brown is an American filmmaker and screenwriter best known for writing and directing the romantic comedy film "Two Can Play That Game."
-
B.
Matt Brown
Matt Brown is an American mixed martial artist and longtime UFC welterweight known for his aggressive, brawling style and high finishing rate.
-
C.
Greg Brown
Greg Brown is an American ice hockey coach and former defenseman best known for leading the Boston College Eagles men's hockey program.
-
D.
Jonathan Brown
Jonathan Brown is a cinematographer best known for his work on major studio comedies and mainstream Hollywood films, including the 2006 reboot of The Pink Panther.
-
E.
Rob Brown
Rob Brown is an American actor best known for his film debut in "Finding Forrester" and his role as a high school basketball player in "Coach Carter."
- 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_69ca82af2d2c8190963861f5e0b8bf21 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cadf22d9b4819081b877c751204a22 |
completed | March 30, 2026, 8:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69caf604715081909eed614cbadb8db6 |
completed | March 30, 2026, 10:15 p.m. |
| NEDg | Description generation | batch_69caf81ff934819094f8089b0bd8dde7 |
completed | March 30, 2026, 10:24 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cafa512e748190a52fe462d3d59f06 |
completed | March 30, 2026, 10:33 p.m. |
Created at: March 30, 2026, 4:23 p.m.