Triple
T15624997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RED (2010 film) |
E375656
|
entity |
| Predicate | title |
P38
|
FINISHED |
| Object | RED |
E375656
|
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: RED | Statement: [RED (2010 film), title, RED]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: RED Context triple: [RED (2010 film), title, RED]
-
A.
RED
RED (Random Early Detection) is an active queue management algorithm used in networking to preemptively drop packets and control congestion before router buffers overflow.
-
B.
RED
chosen
RED is a 2010 action-comedy film about retired black-ops agents who reunite to uncover a conspiracy, known for its ensemble cast including Helen Mirren and Bruce Willis.
-
C.
Red
Red is Virgin America’s signature in-flight entertainment system, offering passengers on-demand movies, TV, music, games, and other interactive services.
-
D.
Red
Red is one of the main playable heroes in the run-and-gun video game Gunstar Heroes, known for fast-paced combat and cooperative action.
-
E.
Red
"Red" is a song featured on the album *Careful Confessions* by singer-songwriter Sara Bareilles.
- 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_69d85cd035a48190b73d5579ab73969a |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e9e5e248190ae54cda1fde51efb |
completed | April 16, 2026, 2:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff678c9d8c8190be73b6e7ed558e99 |
completed | May 9, 2026, 4:57 p.m. |
Created at: April 10, 2026, 4:14 a.m.