Triple
T3982383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UTEP Miners football team |
E86787
|
entity |
| Predicate | teamNickname |
P5076
|
FINISHED |
| Object |
Miners
Miners is the nickname for the University of Texas at El Paso’s athletic teams, most prominently its NCAA Division I football program.
|
E403344
|
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: Miners | Statement: [UTEP Miners football team, teamNickname, Miners]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Miners Context triple: [UTEP Miners football team, teamNickname, Miners]
-
A.
Miner
Miner is a surname of English origin historically associated with the occupation of mining.
-
B.
Gold Mine
"Gold Mine" is a thriller novel by Wilbur Smith that centers on power struggles, greed, and danger in the South African gold mining industry.
-
C.
Placer
Placer is the former historic name of the town now known as Loomis in Placer County, California.
-
D.
The Young Miner
"The Young Miner" is a 19th-century rags-to-riches boys' novel by Horatio Alger Jr. that follows a poor youth striving for success through hard work and perseverance.
-
E.
Mystery Mine
Mystery Mine is a themed steel roller coaster at Dollywood known for its dark ride elements, immersive storytelling, and sudden drops.
- 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: Miners Triple: [UTEP Miners football team, teamNickname, Miners]
Generated description
Miners is the nickname for the University of Texas at El Paso’s athletic teams, most prominently its NCAA Division I football program.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Miners Target entity description: Miners is the nickname for the University of Texas at El Paso’s athletic teams, most prominently its NCAA Division I football program.
-
A.
Miner
Miner is a surname of English origin historically associated with the occupation of mining.
-
B.
Gold Mine
"Gold Mine" is a thriller novel by Wilbur Smith that centers on power struggles, greed, and danger in the South African gold mining industry.
-
C.
Placer
Placer is the former historic name of the town now known as Loomis in Placer County, California.
-
D.
The Young Miner
"The Young Miner" is a 19th-century rags-to-riches boys' novel by Horatio Alger Jr. that follows a poor youth striving for success through hard work and perseverance.
-
E.
Mystery Mine
Mystery Mine is a themed steel roller coaster at Dollywood known for its dark ride elements, immersive storytelling, and sudden drops.
- 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_69aed93fd9d4819085d3b2137d2346cb |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef9db804c8190ad96656cb7b1a4fe |
completed | March 9, 2026, 4:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b540257c188190899b00bf1d0247d2 |
completed | March 14, 2026, 11:01 a.m. |
| NEDg | Description generation | batch_69b54111e5188190ab8ec23124c22981 |
completed | March 14, 2026, 11:05 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b54193105c81909e2a4e368aae36e8 |
completed | March 14, 2026, 11:08 a.m. |
Created at: March 9, 2026, 3:33 p.m.