Triple
T15414267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tha Eastsidaz |
E369172
|
entity |
| Predicate | notableSong |
P4
|
FINISHED |
| Object |
Got Beef
"Got Beef" is a hip hop track by Tha Eastsidaz that showcases the group's West Coast gangsta rap style and street-focused lyricism.
|
E1156112
|
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: Got Beef | Statement: [Tha Eastsidaz, notableSong, Got Beef]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Got Beef Context triple: [Tha Eastsidaz, notableSong, Got Beef]
-
A.
The Beef Carcass
The Beef Carcass is a vivid, expressionistic painting by Chaim Soutine, renowned for its dramatic depiction of a hanging animal carcass that explores themes of mortality and raw physicality.
-
B.
Beef II
Beef II is a documentary film that explores high-profile feuds and rivalries within the hip-hop music industry.
-
C.
Beef III
Beef III is a documentary film that chronicles and analyzes high-profile feuds and conflicts within the hip-hop community.
-
D.
Beyond Beef
Beyond Beef is a plant-based ground meat alternative created by Beyond Meat to mimic the taste and texture of traditional beef.
-
E.
Big Meat
Big Meat is a supporting criminal figure in the 2006 action-crime film "Waist Deep."
- 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: Got Beef Triple: [Tha Eastsidaz, notableSong, Got Beef]
Generated description
"Got Beef" is a hip hop track by Tha Eastsidaz that showcases the group's West Coast gangsta rap style and street-focused lyricism.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Got Beef Target entity description: "Got Beef" is a hip hop track by Tha Eastsidaz that showcases the group's West Coast gangsta rap style and street-focused lyricism.
-
A.
The Beef Carcass
The Beef Carcass is a vivid, expressionistic painting by Chaim Soutine, renowned for its dramatic depiction of a hanging animal carcass that explores themes of mortality and raw physicality.
-
B.
Beef II
Beef II is a documentary film that explores high-profile feuds and rivalries within the hip-hop music industry.
-
C.
Beef III
Beef III is a documentary film that chronicles and analyzes high-profile feuds and conflicts within the hip-hop community.
-
D.
Beyond Beef
Beyond Beef is a plant-based ground meat alternative created by Beyond Meat to mimic the taste and texture of traditional beef.
-
E.
Big Meat
Big Meat is a supporting criminal figure in the 2006 action-crime film "Waist Deep."
- 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_69d85a1849f48190bf898068b2806fae |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03ea7561481909b04e613e2352f82 |
completed | April 16, 2026, 1:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff1a7722a08190af230ecafda30b18 |
completed | May 9, 2026, 11:28 a.m. |
| NEDg | Description generation | batch_69ff1b5a328c81909aaa74c6f002875c |
completed | May 9, 2026, 11:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff1bdb39b481908f0b1df595837bc4 |
completed | May 9, 2026, 11:34 a.m. |
Created at: April 10, 2026, 3:20 a.m.