Triple
T2289436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stripped |
E51468
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Steve Morales
Steve Morales is a music producer known for his work in pop and dance genres, collaborating with various mainstream artists.
|
E252698
|
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: Steve Morales | Statement: [Stripped, producer, Steve Morales]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Steve Morales Context triple: [Stripped, producer, Steve Morales]
-
A.
Lance Briggs
Lance Briggs is a former NFL linebacker best known for his long, Pro Bowl–caliber career with the Chicago Bears.
-
B.
Jeff Cunningham
Jeff Cunningham is a former professional soccer forward best known as one of Major League Soccer’s most prolific goal scorers.
-
C.
John Curtis Estes
John Curtis Estes is the birth name of John Holmes, a notorious American adult film actor who became one of the most famous pornographic performers of the 1970s and 1980s.
-
D.
Mike Sullivan
Mike Sullivan is an American professional ice hockey coach best known for leading the Pittsburgh Penguins to multiple Stanley Cup championships.
-
E.
Connor Murphy
Connor Murphy is a troubled, emotionally unstable teenager whose death becomes the catalyst for the events and moral dilemmas in the musical "Dear Evan Hansen."
- 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: Steve Morales Triple: [Stripped, producer, Steve Morales]
Generated description
Steve Morales is a music producer known for his work in pop and dance genres, collaborating with various mainstream artists.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Steve Morales Target entity description: Steve Morales is a music producer known for his work in pop and dance genres, collaborating with various mainstream artists.
-
A.
Lance Briggs
Lance Briggs is a former NFL linebacker best known for his long, Pro Bowl–caliber career with the Chicago Bears.
-
B.
Jeff Cunningham
Jeff Cunningham is a former professional soccer forward best known as one of Major League Soccer’s most prolific goal scorers.
-
C.
John Curtis Estes
John Curtis Estes is the birth name of John Holmes, a notorious American adult film actor who became one of the most famous pornographic performers of the 1970s and 1980s.
-
D.
Mike Sullivan
Mike Sullivan is an American professional ice hockey coach best known for leading the Pittsburgh Penguins to multiple Stanley Cup championships.
-
E.
Connor Murphy
Connor Murphy is a troubled, emotionally unstable teenager whose death becomes the catalyst for the events and moral dilemmas in the musical "Dear Evan Hansen."
- 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_69a88b09c644819090b503456d96bf70 |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc273b67c8190bcd96f9a484647ef |
completed | March 7, 2026, 6:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae7f1e84ac819096cb62ce5e94d865 |
completed | March 9, 2026, 8:04 a.m. |
| NEDg | Description generation | batch_69ae7fee12ac8190bb9924f7467434a6 |
completed | March 9, 2026, 8:08 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae8061cd348190b0b0b65dcf730f99 |
completed | March 9, 2026, 8:10 a.m. |
Created at: March 4, 2026, 7:48 p.m.