Triple
T3771994
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Black Sunday |
E83218
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Tom Rolf |
E214378
|
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: Tom Rolf | Statement: [Black Sunday, editedBy, Tom Rolf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom Rolf Context triple: [Black Sunday, editedBy, Tom Rolf]
-
A.
Tom Rolf
chosen
Tom Rolf was an American film editor best known for his work on acclaimed movies such as "Taxi Driver" and for winning an Academy Award for editing "The Right Stuff."
-
B.
Ron Hagen
Ron Hagen is a cinematographer best known for his work on the Australian film "Romper Stomper."
-
C.
Curt Rothenberger
Curt Rothenberger was a German jurist and high-ranking Nazi official who played a key role in implementing and justifying the Third Reich’s oppressive legal policies.
-
D.
Bob Suter
Bob Suter was an American defenseman best known as a member of the "Miracle on Ice" 1980 U.S. Olympic hockey team and later a prominent youth hockey coach and scout.
-
E.
Joe Klotz
Joe Klotz is an American film editor best known for his acclaimed work on the drama film "Precious."
- 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_69ad8b235e608190b5a2b1d1bfcef50b |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcc3219b881908a2f82126f9a679d |
completed | March 8, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4f039cd9c81908ea1428f2c328cdb |
completed | March 14, 2026, 5:20 a.m. |
Created at: March 8, 2026, 3:36 p.m.