Triple
T513366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Auerbach |
E10653
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object |
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.
|
E63964
|
NE FINISHED |
How this triple was built (4 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 Auerbach, nickname, Red]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Red Context triple: [Red Auerbach, nickname, Red]
-
A.
Crimson
Crimson is the collective name for Harvard University's varsity athletic teams competing in collegiate sports.
-
B.
Orange
Orange is a historic town in southeastern France best known for giving its name and origin to the Dutch royal House of Orange-Nassau.
-
C.
Black-and-Red
Black-and-Red is the widely used nickname for Major League Soccer club D.C. United, referencing the team’s traditional colors and identity.
-
D.
Red 1
Red 1 is the callsign used by the team leader of the Royal Air Force's Red Arrows aerobatic display team.
-
E.
Blue
Blue is a critically acclaimed 1971 folk album by Joni Mitchell, widely regarded as one of the greatest and most influential records in popular music history.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Red Triple: [Red Auerbach, nickname, Red]
Generated description
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.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Red Target entity description: 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.
-
A.
Crimson
Crimson is the collective name for Harvard University's varsity athletic teams competing in collegiate sports.
-
B.
Orange
Orange is a historic town in southeastern France best known for giving its name and origin to the Dutch royal House of Orange-Nassau.
-
C.
Black-and-Red
Black-and-Red is the widely used nickname for Major League Soccer club D.C. United, referencing the team’s traditional colors and identity.
-
D.
Red 1
Red 1 is the callsign used by the team leader of the Royal Air Force's Red Arrows aerobatic display team.
-
E.
Blue
Blue is a critically acclaimed 1971 folk album by Joni Mitchell, widely regarded as one of the greatest and most influential records in popular music history.
- F. None of above. chosen
Provenance (5 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_69a2e84a0d08819087e01863fcd9abf1 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f1804e908190a1d34ac952e84a3f |
completed | Feb. 28, 2026, 1:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4a14f9cc88190ada7a80d5f8ec6fc |
completed | March 1, 2026, 8:27 p.m. |
| NEDg | Description generation | batch_69a4a1c63d34819085387882bbc67041 |
completed | March 1, 2026, 8:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a4a223c5ec8190a239d548e8c68960 |
completed | March 1, 2026, 8:31 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.