Triple
T5651163
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Western New England University |
E124511
|
entity |
| Predicate | hasMascot |
P52
|
FINISHED |
| Object |
Golden Bear
Golden Bear is the mascot representing Western New England University’s athletic teams and school spirit.
|
E535382
|
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: Golden Bear | Statement: [Western New England University, hasMascot, Golden Bear]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Golden Bear Context triple: [Western New England University, hasMascot, Golden Bear]
-
A.
Golden Bear
The Golden Bear is the top prize awarded to the best film at the prestigious Berlin International Film Festival, one of the world’s major annual film festivals.
-
B.
Golden Lion
The Golden Lion is the top prize awarded for the best film at the prestigious Venice Film Festival.
-
C.
Oscar
The Oscar is a prestigious film industry award presented annually by the Academy of Motion Picture Arts and Sciences to honor outstanding cinematic achievements.
-
D.
Oscar
Oscar is a masculine given name of Old English and Norse origin, commonly used in many European and English-speaking countries.
-
E.
Oscar
Oscar is the Allied reporting name for the Nakajima Ki-43, a Japanese World War II fighter aircraft used extensively by the Imperial Japanese Army Air Service.
- 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: Golden Bear Triple: [Western New England University, hasMascot, Golden Bear]
Generated description
Golden Bear is the mascot representing Western New England University’s athletic teams and school spirit.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Golden Bear Target entity description: Golden Bear is the mascot representing Western New England University’s athletic teams and school spirit.
-
A.
Golden Bear
The Golden Bear is the top prize awarded to the best film at the prestigious Berlin International Film Festival, one of the world’s major annual film festivals.
-
B.
Golden Lion
The Golden Lion is the top prize awarded for the best film at the prestigious Venice Film Festival.
-
C.
Oscar
The Oscar is a prestigious film industry award presented annually by the Academy of Motion Picture Arts and Sciences to honor outstanding cinematic achievements.
-
D.
Oscar
Oscar is a masculine given name of Old English and Norse origin, commonly used in many European and English-speaking countries.
-
E.
Oscar
Oscar is the Allied reporting name for the Nakajima Ki-43, a Japanese World War II fighter aircraft used extensively by the Imperial Japanese Army Air Service.
- 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_69c00825df388190a58742fa9b1aa33d |
completed | March 22, 2026, 3:17 p.m. |
| NER | Named-entity recognition | batch_69c022d6af9481909eaeead2a39525ce |
completed | March 22, 2026, 5:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c04d90c04881908740fb1089c5248a |
completed | March 22, 2026, 8:14 p.m. |
| NEDg | Description generation | batch_69c04edcc0208190bd69b5cce89596f9 |
completed | March 22, 2026, 8:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c04ff814b88190ad01844ae2629c6e |
completed | March 22, 2026, 8:24 p.m. |
Created at: March 22, 2026, 3:42 p.m.