Triple
T12295835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ultra Panavision 70 |
E293083
|
entity |
| Predicate | relatedFormat |
P26987
|
FINISHED |
| Object | Todd-AO |
E55677
|
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: Todd-AO | Statement: [Ultra Panavision 70, relatedFormat, Todd-AO]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Todd-AO Context triple: [Ultra Panavision 70, relatedFormat, Todd-AO]
-
A.
Todd-AO
chosen
Todd-AO is a high-resolution widescreen motion picture film format and production system developed in the 1950s to provide an immersive, large-screen cinematic experience.
-
B.
Todd
Todd is the maiden surname of Mary Todd Lincoln, the First Lady of the United States during Abraham Lincoln’s presidency.
-
C.
AO
AO is the two-letter ISO 3166-1 alpha-2 country code representing Angola in international standards and systems.
-
D.
AO
AO is a UK-based online electricals retailer known for selling appliances and consumer electronics through its e-commerce platform and associated services.
-
E.
AO
AO is the vehicle registration code used on license plates for vehicles registered in Italy’s Aosta Valley region.
- 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_69d6ab690ad081908c0ed3870ec82d53 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93ed903808190b7ed90e0db3d7586 |
completed | April 10, 2026, 6:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f61e79bf548190bf7f314222ed1ed1 |
completed | May 2, 2026, 3:55 p.m. |
Created at: April 8, 2026, 9:52 p.m.