Triple
T9432289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William L. "Red" Whittaker |
E227410
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object | Red |
E147627
|
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: [William L. "Red" Whittaker, nickname, Red]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Red Context triple: [William L. "Red" Whittaker, nickname, Red]
-
A.
Red
Red is Virgin America’s signature in-flight entertainment system, offering passengers on-demand movies, TV, music, games, and other interactive services.
-
B.
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.
-
C.
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.
-
D.
Red
chosen
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 nickname of Red Rolfe, an American Major League Baseball third baseman best known for his years with the New York Yankees in the 1930s and 1940s.
- 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_69ca8437a7ac81908651de48f2d2141d |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd7e6059bc8190a7e98aef3caabd0b |
completed | April 1, 2026, 8:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d15261b31881908c1059d704e56bf6 |
completed | April 4, 2026, 6:03 p.m. |
Created at: March 30, 2026, 7:49 p.m.