Triple
T7878369
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chicago Wolves |
E182912
|
entity |
| Predicate | teamNameIncludes |
P79531
|
FINISHED |
| Object |
Wolves
Wolves is the shared name of various professional and amateur sports teams, most notably used by the Chicago Wolves ice hockey franchise.
|
E701076
|
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: Wolves | Statement: [Chicago Wolves, teamNameIncludes, Wolves]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wolves Context triple: [Chicago Wolves, teamNameIncludes, Wolves]
-
A.
Wolves
"Wolves" is a moody, atmospheric hip-hop track by Kanye West that blends haunting production with introspective lyrics and prominent guest vocals.
-
B.
Wolves
Wolves is the athletic nickname and mascot representing the sports teams of Western Oregon University.
-
C.
Wolves
Wolves is the commonly used nickname for the NBA’s Minnesota Timberwolves basketball team.
-
D.
Wolves
Wolves is the commonly used name for Wolverhampton Wanderers Football Club, a professional English football team based in Wolverhampton that competes in the Premier League.
-
E.
Wolves
Wolves is the commonly used short name for the Warrington Wolves, a professional rugby league club based in Warrington, England.
- 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: Wolves Triple: [Chicago Wolves, teamNameIncludes, Wolves]
Generated description
Wolves is the shared name of various professional and amateur sports teams, most notably used by the Chicago Wolves ice hockey franchise.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wolves Target entity description: Wolves is the shared name of various professional and amateur sports teams, most notably used by the Chicago Wolves ice hockey franchise.
-
A.
Wolves
chosen
Wolves is the short name of the Chicago Wolves, a professional ice hockey team based in the Chicago metropolitan area that competes in the American Hockey League.
-
B.
Wolves
Wolves is the commonly used nickname for the NBA’s Minnesota Timberwolves basketball team.
-
C.
Wolves
Wolves is the commonly used name for Wolverhampton Wanderers Football Club, a professional English football team based in Wolverhampton that competes in the Premier League.
-
D.
Wolves
Wolves is the commonly used short name for the Warrington Wolves, a professional rugby league club based in Warrington, England.
-
E.
Wolves
Wolves is the athletic nickname and mascot representing the sports teams of Western Oregon University.
- F. None of above.
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_69ca828a17248190b46defe758bc5ad3 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb39bd64e481909f699e7dd2818b8f |
completed | March 31, 2026, 3:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbdfa64c148190bf2b872bbfda1b3e |
completed | March 31, 2026, 2:52 p.m. |
| NEDg | Description generation | batch_69cc46bca04481908852425c214a4e34 |
completed | March 31, 2026, 10:12 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cc49129e188190aaebd6a1188788d9 |
completed | March 31, 2026, 10:22 p.m. |
Created at: March 30, 2026, 4:57 p.m.