Triple
T6003147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Butler Blue |
E133643
|
entity |
| Predicate | hasTitle |
P38
|
FINISHED |
| Object | Butler Blue II |
E133643
|
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: Butler Blue II | Statement: [Butler Blue, hasTitle, Butler Blue II]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Butler Blue II Context triple: [Butler Blue, hasTitle, Butler Blue II]
-
A.
Butler Blue
chosen
Butler Blue is the live English bulldog that serves as the beloved mascot of Butler University and its athletic teams.
-
B.
Butler
Butler is the party that served as the defendant in the landmark U.S. Supreme Court case United States v. Butler, which addressed the constitutionality of certain New Deal agricultural policies.
-
C.
Butler
Butler is a city in Pennsylvania that serves as the administrative and economic center of Butler County.
-
D.
Butler
Butler is a common English and Irish surname historically associated with nobility and service roles, borne by numerous notable figures in politics, law, and the arts.
-
E.
Porter
Porter is a common English occupational surname historically given to gatekeepers or doorkeepers.
- 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_69c00872444c8190bfaf1739dcec765c |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04f0f63148190826198281dce3713 |
completed | March 22, 2026, 8:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c11365741c819097a43a49dd2428c1 |
completed | March 23, 2026, 10:18 a.m. |
Created at: March 22, 2026, 4:06 p.m.