Triple
T1785459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Big 5 basketball |
E39380
|
entity |
| Predicate | hasNickname |
P39
|
FINISHED |
| Object |
City Series
City Series is the popular nickname for the historic Big 5 college basketball rivalry among Philadelphia-area universities.
|
E198204
|
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: City Series | Statement: [Big 5 basketball, hasNickname, City Series]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: City Series Context triple: [Big 5 basketball, hasNickname, City Series]
-
A.
City SC
City SC is a Major League Soccer club based in St. Louis, Missouri, known for its vibrant fan culture and status as one of the league’s newest expansion teams.
-
B.
City Torque
City Torque is a Uruguayan professional football club based in Montevideo that competes in the country’s top divisions.
-
C.
Red City
Red City is a popular nickname for Marrakesh, the historic Moroccan metropolis famed for its reddish sandstone buildings and city walls.
-
D.
Hoop City
Hoop City is a nickname for Springfield, Massachusetts, highlighting its rich basketball history and status as the birthplace of the sport.
-
E.
City Loop
City Loop is Melbourne’s central underground railway system that circulates suburban trains through key inner-city stations.
- 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: City Series Triple: [Big 5 basketball, hasNickname, City Series]
Generated description
City Series is the popular nickname for the historic Big 5 college basketball rivalry among Philadelphia-area universities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: City Series Target entity description: City Series is the popular nickname for the historic Big 5 college basketball rivalry among Philadelphia-area universities.
-
A.
City SC
City SC is a Major League Soccer club based in St. Louis, Missouri, known for its vibrant fan culture and status as one of the league’s newest expansion teams.
-
B.
City Torque
City Torque is a Uruguayan professional football club based in Montevideo that competes in the country’s top divisions.
-
C.
Red City
Red City is a popular nickname for Marrakesh, the historic Moroccan metropolis famed for its reddish sandstone buildings and city walls.
-
D.
Hoop City
Hoop City is a nickname for Springfield, Massachusetts, highlighting its rich basketball history and status as the birthplace of the sport.
-
E.
City Loop
City Loop is Melbourne’s central underground railway system that circulates suburban trains through key inner-city stations.
- 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_69a88630519c8190a17addd83c4a3ef4 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa650d304481908ad9bff3eadf7da6 |
completed | March 6, 2026, 5:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ada9a476448190b072361fe4b41537 |
completed | March 8, 2026, 4:53 p.m. |
| NEDg | Description generation | batch_69adab05cf6c81909f4713664f508ad9 |
completed | March 8, 2026, 4:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adaeb20390819098bad8951ec00d00 |
completed | March 8, 2026, 5:15 p.m. |
Created at: March 4, 2026, 7:31 p.m.