Triple
T13238531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Romeo Is Bleeding |
E315217
|
entity |
| Predicate | director |
P255
|
FINISHED |
| Object | Peter Medak |
E460219
|
NE FINISHED |
How this triple was built (2 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 Medak | Statement: [Romeo Is Bleeding, director, Peter Medak]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Medak Context triple: [Romeo Is Bleeding, director, Peter Medak]
-
A.
Peter Medak
chosen
Peter Medak is a Hungarian-born British film and television director known for works such as the crime biopic "The Krays" and the horror classic "The Changeling."
-
B.
Thomas Kostura
Thomas Kostura is an individual known for being a plaintiff in the landmark same-sex marriage recognition case Tanco v. Haslam in Tennessee.
-
C.
Martin Pasko
Martin Pasko was an American comic book and television writer best known for his work on DC Comics characters, particularly Superman and Batman, and for contributing to various animated series.
-
D.
George Kralovansky
George Kralovansky is a television producer best known for his executive production work on the live law-enforcement reality series "Live PD."
-
E.
Paul Koslo
Paul Koslo was a German-Canadian character actor known for his supporting roles in 1970s and 1980s action and science fiction films.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d806b1072881909e46bd212259c5f0 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98d5850ac8190849a51da39efe5be |
completed | April 10, 2026, 11:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f70a38d09881909e8e3c32e9b1746e |
completed | May 3, 2026, 8:41 a.m. |
Created at: April 9, 2026, 9:23 p.m.