Triple
T9937144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Mighty Heart |
E193986
|
entity |
| Predicate | cinematographer |
P1953
|
FINISHED |
| Object | Marcel Zyskind |
E254602
|
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: Marcel Zyskind | Statement: [A Mighty Heart, cinematographer, Marcel Zyskind]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marcel Zyskind Context triple: [A Mighty Heart, cinematographer, Marcel Zyskind]
-
A.
Marcel Zyskind
chosen
Marcel Zyskind is a Danish cinematographer known for his visually distinctive work on independent and art-house films.
-
B.
Bernard Zehrfuss
Bernard Zehrfuss was a prominent 20th-century French architect known for his modernist public and institutional buildings.
-
C.
René Havard
René Havard was a French screenwriter and actor active in mid-20th-century cinema.
-
D.
Pierre Messmer
Pierre Messmer was a French Gaullist politician and statesman who served as Prime Minister of France in the early 1970s and held several key ministerial posts during the Fifth Republic.
-
E.
Henri Zuber
Henri Zuber was a 19th-century French painter and watercolorist known for his landscapes and Orientalist scenes.
- 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_69ca82e409348190a393777356b80a2a |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb5e4e19881909879b394090d6629 |
completed | April 2, 2026, 12:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d74fb63b7081909cb6faddd795ced6 |
completed | April 9, 2026, 7:05 a.m. |
Created at: March 30, 2026, 8:44 p.m.