Triple
T9925279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rey |
E187905
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object | Rages |
E438449
|
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: Rages | Statement: [Rey, hasAlternativeName, Rages]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rages Context triple: [Rey, hasAlternativeName, Rages]
-
A.
Rages
chosen
Rages is an alternative name for the figure or entity known as Rayy.
-
B.
The Rage
The Rage is a 2007 American horror film directed by special effects artist Robert Kurtzman, known for its gruesome practical effects and over-the-top gore.
-
C.
Frenzy
Frenzy is a 1972 British thriller film directed by Alfred Hitchcock, known for its dark humor and disturbing portrayal of a serial killer in London.
-
D.
Frenzy
"Frenzy" is a popular Nigerian Afropop song by artist D'Prince, known for its energetic beat and club-friendly vibe.
-
E.
Rage
Rage is a Japanese crime drama film featuring Ken Watanabe in a central role, exploring the aftermath of a brutal murder and the corrosive effects of suspicion on human relationships.
- 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_69ca82b22a688190b52c75bd48429c10 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cdb598651081908286763ff56ba57c |
completed | April 2, 2026, 12:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d20e143660819097a9fa96365bc25a |
completed | April 5, 2026, 7:24 a.m. |
Created at: March 30, 2026, 8:43 p.m.