Triple
T6446844
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robbie Lawler |
E138362
|
entity |
| Predicate | hasFought |
P30824
|
FINISHED |
| Object |
Matt Brown
Matt Brown is an American mixed martial artist and longtime UFC welterweight known for his aggressive, brawling style and high finishing rate.
|
E594842
|
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: Matt Brown | Statement: [Robbie Lawler, hasFought, Matt Brown]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matt Brown Context triple: [Robbie Lawler, hasFought, Matt 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 Wolpert
Matt Wolpert is a television writer and producer best known for co-creating the alternate-history space drama series "For All Mankind."
-
C.
Michael Pitts
Michael Pitts is a relatively common personal name shared by multiple individuals, including figures in fields such as politics, religion, and entertainment.
-
D.
Matt Chesse
Matt Chesse is an American film editor known for his work on numerous feature films, including the thriller "Money Monster."
-
E.
Jason Shuman
Jason Shuman is a film and television producer known for his work on projects such as the sports drama series "Winning Time: The Rise of the Lakers Dynasty."
- 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: Matt Brown Triple: [Robbie Lawler, hasFought, Matt Brown]
Generated description
Matt Brown is an American mixed martial artist and longtime UFC welterweight known for his aggressive, brawling style and high finishing rate.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Matt Brown Target entity description: Matt Brown is an American mixed martial artist and longtime UFC welterweight known for his aggressive, brawling style and high finishing rate.
-
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 Wolpert
Matt Wolpert is a television writer and producer best known for co-creating the alternate-history space drama series "For All Mankind."
-
C.
Michael Pitts
Michael Pitts is a relatively common personal name shared by multiple individuals, including figures in fields such as politics, religion, and entertainment.
-
D.
Matt Chesse
Matt Chesse is an American film editor known for his work on numerous feature films, including the thriller "Money Monster."
-
E.
Jason Shuman
Jason Shuman is a film and television producer known for his work on projects such as the sports drama series "Winning Time: The Rise of the Lakers Dynasty."
- 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_69c008aa61ac8190bc96715ed79fe2d8 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0698edeac81909426902471d8a57b |
completed | March 22, 2026, 10:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c64bcd09e0819097eb60d13e8058dd |
completed | March 27, 2026, 9:20 a.m. |
| NEDg | Description generation | batch_69c64fba85a08190ad270b010294f86a |
completed | March 27, 2026, 9:36 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6508c2fb481909da94b4f67e95ecf |
completed | March 27, 2026, 9:40 a.m. |
Created at: March 22, 2026, 4:46 p.m.