Triple
T8449410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Hit |
E199763
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object |
Peter Prince
Peter Prince is a writer best known for his work on the film "The Hit."
|
E735034
|
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: Peter Prince | Statement: [The Hit, writer, Peter Prince]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Prince Context triple: [The Hit, writer, Peter Prince]
-
A.
Peter Anthony Prince
Peter Anthony Prince was a prominent early Calgary lumber entrepreneur and community figure after whom Prince's Island Park is named.
-
B.
Matthew Prince
Matthew Prince is an American technology entrepreneur best known as the co-founder and CEO of the internet security and performance company Cloudflare.
-
C.
Benjamin Parker
Benjamin Parker, commonly known as Uncle Ben, is a pivotal father-figure in Spider-Man’s origin story whose death profoundly shapes Peter Parker’s sense of responsibility.
-
D.
Peter Kingdom
Peter Kingdom is the mild-mannered, compassionate solicitor protagonist of the British television drama series "Kingdom," set in a small Norfolk town.
-
E.
Wally Westmore
Wally Westmore was a prominent Hollywood makeup artist known for his influential work during the mid-20th century, particularly at Paramount Pictures.
- 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: Peter Prince Triple: [The Hit, writer, Peter Prince]
Generated description
Peter Prince is a writer best known for his work on the film "The Hit."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Peter Prince Target entity description: Peter Prince is a writer best known for his work on the film "The Hit."
-
A.
Peter Anthony Prince
Peter Anthony Prince was a prominent early Calgary lumber entrepreneur and community figure after whom Prince's Island Park is named.
-
B.
Matthew Prince
Matthew Prince is an American technology entrepreneur best known as the co-founder and CEO of the internet security and performance company Cloudflare.
-
C.
Benjamin Parker
Benjamin Parker, commonly known as Uncle Ben, is a pivotal father-figure in Spider-Man’s origin story whose death profoundly shapes Peter Parker’s sense of responsibility.
-
D.
Peter Kingdom
Peter Kingdom is the mild-mannered, compassionate solicitor protagonist of the British television drama series "Kingdom," set in a small Norfolk town.
-
E.
Wally Westmore
Wally Westmore was a prominent Hollywood makeup artist known for his influential work during the mid-20th century, particularly at Paramount Pictures.
- 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_69ca83170f9081909cd98f55614c6476 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe44707b88190b3d8b30c45ef4496 |
completed | March 31, 2026, 3:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce1dc85e48819083340d022d0dba9b |
completed | April 2, 2026, 7:42 a.m. |
| NEDg | Description generation | batch_69ce1f88d404819096c6024c0e61d1ea |
completed | April 2, 2026, 7:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce209338b48190ba8375200a5529bd |
completed | April 2, 2026, 7:53 a.m. |
Created at: March 30, 2026, 6:09 p.m.