Triple
T6043212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Schwentke |
E134598
|
entity |
| Predicate | notableWork |
P4
|
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: [Robert Schwentke, notableWork, RED]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: RED Context triple: [Robert Schwentke, notableWork, 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 the famous nickname of Arnold "Red" Auerbach, the legendary Boston Celtics coach and executive known for his pivotal role in building an NBA dynasty.
-
D.
Red
Red is the nickname of William L. "Red" Whittaker, a pioneering American roboticist known for his work in field robotics and autonomous vehicles.
-
E.
Red
Red is the tough, sharp-tongued Russian matriarch and prison cook from the television series "Orange Is the New Black."
- 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_69c00876a69881908088a2626d3b2666 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c056e108fc81908775d176ff960fad |
completed | March 22, 2026, 8:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1139b44888190bfa12d19e99ee673 |
completed | March 23, 2026, 10:19 a.m. |
Created at: March 22, 2026, 4:08 p.m.