Triple
T15426011
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City of Madison |
E369510
|
entity |
| Predicate | hasNickname |
P39
|
FINISHED |
| Object | Madtown |
E1101042
|
NE FINISHED |
How this triple was built (2 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: Madtown | Statement: [City of Madison, hasNickname, Madtown]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Madtown Context triple: [City of Madison, hasNickname, Madtown]
-
A.
Madtown
chosen
Madtown is a popular nickname for Madison, Wisconsin, known for its vibrant college-town atmosphere, progressive politics, and lakeside setting.
-
B.
Red Town
Red Town is a historical region associated with the settlement of Krasnaya Sloboda, known for its cultural and regional significance.
-
C.
In the Hood
"In the Hood" is a gritty hip-hop track by Wu-Tang Clan that reflects street life themes and appears on their album "Iron Flag."
-
D.
Boogie Down
"Boogie Down" is a 1983 R&B/disco single by former Temptations singer Eddie Kendricks that became one of his best-known solo hits.
-
E.
Boogie Down
Boogie Down is a soul and R&B song by American singer-songwriter and producer Frank Wilson, recognized as one of his notable recordings.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d85a1849f48190bf898068b2806fae |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03ec1fb288190a3625b8e4f487dd1 |
completed | April 16, 2026, 1:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff1a7ed0ec8190b8086f78df965b61 |
completed | May 9, 2026, 11:29 a.m. |
Created at: April 10, 2026, 3:20 a.m.