Triple
T15579321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Co-Star Mode |
E374450
|
entity |
| Predicate | relatedCharacter |
P37304
|
FINISHED |
| Object | Luma |
E75273
|
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: Luma | Statement: [Co-Star Mode, relatedCharacter, Luma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Luma Context triple: [Co-Star Mode, relatedCharacter, Luma]
-
A.
Luma
chosen
Luma is a small, star-shaped celestial creature from the Super Mario series, known for its cute appearance and connection to Rosalina and the cosmos.
-
B.
Lumo
Lumo is a British open-access train operator running low-cost, long-distance electric services on the East Coast Main Line between London and northeastern England.
-
C.
Luz
Luz is a major railway and metro hub in São Paulo, Brazil, serving as a key interchange point for multiple urban transit lines.
-
D.
Luz
Luz was the nickname of Carl Ludwig Long, a German long jumper best known for his sportsmanship toward Jesse Owens at the 1936 Berlin Olympics.
-
E.
Luz
Luz is a small coastal settlement on Graciosa Island in Portugal’s Azores archipelago.
- 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_69d85ccd575081908909b71a3f3e3a61 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e24064c8190b132c3092877fbfa |
completed | April 16, 2026, 2:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff7563674c81908b035a7672b2827d |
completed | May 9, 2026, 5:56 p.m. |
Created at: April 10, 2026, 4:11 a.m.