Triple
T7494884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cool Runnings |
E177097
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Dawn Steel |
E81992
|
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: Dawn Steel | Statement: [Cool Runnings, producer, Dawn Steel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dawn Steel Context triple: [Cool Runnings, producer, Dawn Steel]
-
A.
Dawn Steel
chosen
Dawn Steel was a pioneering American film executive and producer, known as one of the first women to head a major Hollywood studio.
-
B.
Dawn
Dawn is a feminine given name commonly associated with the early morning time when light first appears in the sky.
-
C.
Dawn
Dawn is a modernist sculpture featured in Ludwig Mies van der Rohe’s iconic Barcelona Pavilion.
-
D.
Dawn
Dawn was a NASA space probe that studied the protoplanet Vesta and the dwarf planet Ceres in the asteroid belt using ion propulsion.
-
E.
Dawn
Dawn is a novel by Elie Wiesel that explores the moral and psychological struggles of a young Holocaust survivor involved in a Jewish underground movement in British-controlled Palestine.
- 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_69c69f2583808190bd1a4936c42a5815 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f57b5b4c8190ab839e6a98ee86ed |
completed | March 27, 2026, 9:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c83c819f00819087fef27e4f4fdc1c |
completed | March 28, 2026, 8:39 p.m. |
Created at: March 27, 2026, 3:43 p.m.