Triple
T21537029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Stolen |
E531373
|
entity |
| Predicate | musicBy |
P1952
|
FINISHED |
| Object |
Lance Gurisik
Lance Gurisik is a composer and musician known for creating the musical score for the film "The Stolen."
|
E1499036
|
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: Lance Gurisik | Statement: [The Stolen, musicBy, Lance Gurisik]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lance Gurisik Context triple: [The Stolen, musicBy, Lance Gurisik]
-
A.
Darren Lemke
Darren Lemke is an American screenwriter and film producer known for working on fantasy and adventure films such as Jack the Giant Slayer and the Goosebumps movie adaptation.
-
B.
Greg Ganske
Greg Ganske is an American plastic surgeon and Republican politician who represented Iowa in the U.S. House of Representatives from 1995 to 2003.
-
C.
Gregg Garrison
Gregg Garrison was an American television producer and director best known for his work on variety and music programs during the early decades of TV.
-
D.
Greg DePaul
Greg DePaul is an American screenwriter and playwright best known for co-writing the romantic comedy film "Bride Wars."
-
E.
Brad Goreski
Brad Goreski is a Canadian-American celebrity fashion stylist and television personality known for his sharp red-carpet commentary and appearances on style-focused TV shows.
- 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: Lance Gurisik Triple: [The Stolen, musicBy, Lance Gurisik]
Generated description
Lance Gurisik is a composer and musician known for creating the musical score for the film "The Stolen."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lance Gurisik Target entity description: Lance Gurisik is a composer and musician known for creating the musical score for the film "The Stolen."
-
A.
Darren Lemke
Darren Lemke is an American screenwriter and film producer known for working on fantasy and adventure films such as Jack the Giant Slayer and the Goosebumps movie adaptation.
-
B.
Greg Ganske
Greg Ganske is an American plastic surgeon and Republican politician who represented Iowa in the U.S. House of Representatives from 1995 to 2003.
-
C.
Gregg Garrison
Gregg Garrison was an American television producer and director best known for his work on variety and music programs during the early decades of TV.
-
D.
Greg DePaul
Greg DePaul is an American screenwriter and playwright best known for co-writing the romantic comedy film "Bride Wars."
-
E.
Brad Goreski
Brad Goreski is a Canadian-American celebrity fashion stylist and television personality known for his sharp red-carpet commentary and appearances on style-focused TV shows.
- 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_69e0c45e5b8881908ac18fc2f493b114 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee9d0e5a9c8190894ec3666d3296aa |
completed | April 26, 2026, 11:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a2ebc817c81908c14a3974c50ff63 |
completed | May 17, 2026, 9:10 p.m. |
| NEDg | Description generation | batch_6a0a2f6273ac8190b68980c9c42aa6c0 |
completed | May 17, 2026, 9:13 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a2fc4470481908e897e056cb7d09e |
completed | May 17, 2026, 9:14 p.m. |
Created at: April 16, 2026, 6:27 p.m.