Triple
T6528023
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RPI Engineers men's ice hockey |
E151354
|
entity |
| Predicate | formerNickname |
P65
|
FINISHED |
| Object |
Cherry and White
Cherry and White was an early nickname for the Rensselaer Polytechnic Institute men's ice hockey team, referencing the school’s traditional colors.
|
E606143
|
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: Cherry and White | Statement: [RPI Engineers men's ice hockey, formerNickname, Cherry and White]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cherry and White Context triple: [RPI Engineers men's ice hockey, formerNickname, Cherry and White]
-
A.
Cherry
Cherry is a song by the electronic rock duo Ratatat, known for its melodic guitar lines and atmospheric, instrumental style.
-
B.
Cherry
Cherry is a common English surname borne by various individuals, including American actor Jake Cherry.
-
C.
Case White
Case White was the German codename for the 1939 invasion of Poland that marked the beginning of World War II in Europe.
-
D.
Blanc
Blanc is the surname of Mel Blanc, the legendary American voice actor best known for bringing to life many iconic Looney Tunes characters.
-
E.
Borouge
Borouge is a leading petrochemicals company based in the United Arab Emirates, specializing in the production of polyolefins for packaging, infrastructure, and industrial applications.
- 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: Cherry and White Triple: [RPI Engineers men's ice hockey, formerNickname, Cherry and White]
Generated description
Cherry and White was an early nickname for the Rensselaer Polytechnic Institute men's ice hockey team, referencing the school’s traditional colors.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Cherry and White Target entity description: Cherry and White was an early nickname for the Rensselaer Polytechnic Institute men's ice hockey team, referencing the school’s traditional colors.
-
A.
Cherry
Cherry is a song by the electronic rock duo Ratatat, known for its melodic guitar lines and atmospheric, instrumental style.
-
B.
Cherry
Cherry is a common English surname borne by various individuals, including American actor Jake Cherry.
-
C.
Case White
Case White was the German codename for the 1939 invasion of Poland that marked the beginning of World War II in Europe.
-
D.
Blanc
Blanc is the surname of Mel Blanc, the legendary American voice actor best known for bringing to life many iconic Looney Tunes characters.
-
E.
Borouge
Borouge is a leading petrochemicals company based in the United Arab Emirates, specializing in the production of polyolefins for packaging, infrastructure, and industrial applications.
- 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_69c687f522748190b3058405553cdabd |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6ada9c8408190b1bc327985366be9 |
completed | March 27, 2026, 4:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6d52a642c8190a50988f3faf61d39 |
completed | March 27, 2026, 7:06 p.m. |
| NEDg | Description generation | batch_69c6d6745b40819083fbcb2a4063e34d |
completed | March 27, 2026, 7:11 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6d830ed6c8190a39126d97a5246d3 |
completed | March 27, 2026, 7:19 p.m. |
Created at: March 27, 2026, 1:46 p.m.