Triple
T20614394
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indianapolis Ice |
E506527
|
entity |
| Predicate | successorTeamInCity |
P45971
|
FINISHED |
| Object |
Indiana Ice
Indiana Ice was a junior ice hockey team based in Indianapolis that competed in the United States Hockey League (USHL).
|
E1441688
|
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: Indiana Ice | Statement: [Indianapolis Ice, successorTeamInCity, Indiana Ice]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Indiana Ice Context triple: [Indianapolis Ice, successorTeamInCity, Indiana Ice]
-
A.
Vilas
Vilas is the surname of Guillermo Vilas, the legendary Argentine tennis player renowned for his clay-court dominance in the 1970s.
-
B.
Wisco
Wisco is an informal nickname commonly used to refer to the University of Wisconsin or the state of Wisconsin.
-
C.
Great Lakes, Illinois
Great Lakes, Illinois is a community best known as the home of the U.S. Navy’s primary training center, including its main boot camp.
-
D.
Interlac
Interlac is a fictional universal translation language used by various alien species and civilizations in the DC Comics universe.
-
E.
Ladoga, Indiana
Ladoga, Indiana is a small town in Montgomery County known as the birthplace of former U.S. Secretary of Agriculture Earl Butz.
- 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: Indiana Ice Triple: [Indianapolis Ice, successorTeamInCity, Indiana Ice]
Generated description
Indiana Ice was a junior ice hockey team based in Indianapolis that competed in the United States Hockey League (USHL).
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Indiana Ice Target entity description: Indiana Ice was a junior ice hockey team based in Indianapolis that competed in the United States Hockey League (USHL).
-
A.
Vilas
Vilas is the surname of Guillermo Vilas, the legendary Argentine tennis player renowned for his clay-court dominance in the 1970s.
-
B.
Wisco
Wisco is an informal nickname commonly used to refer to the University of Wisconsin or the state of Wisconsin.
-
C.
Great Lakes, Illinois
Great Lakes, Illinois is a community best known as the home of the U.S. Navy’s primary training center, including its main boot camp.
-
D.
Interlac
Interlac is a fictional universal translation language used by various alien species and civilizations in the DC Comics universe.
-
E.
Ladoga, Indiana
Ladoga, Indiana is a small town in Montgomery County known as the birthplace of former U.S. Secretary of Agriculture Earl Butz.
- 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_69e0b4bc90988190ac360aaf645efc1d |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6aada19e481909363428ceda67603 |
completed | April 20, 2026, 10:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08bb13545c8190afcd6b35e2aa56ef |
completed | May 16, 2026, 6:44 p.m. |
| NEDg | Description generation | batch_6a08bbb570f4819093e23b20fd83d101 |
completed | May 16, 2026, 6:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08bf7d661c8190af9e9b7b4121f951 |
completed | May 16, 2026, 7:03 p.m. |
Created at: April 16, 2026, 11:41 a.m.