Triple
T16037266
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Big C |
E388999
|
entity |
| Predicate | hasTitle |
P38
|
FINISHED |
| Object | Big C |
E388999
|
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: Big C | Statement: [Big C, hasTitle, Big C]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Big C Context triple: [Big C, hasTitle, Big C]
-
A.
Big C
chosen
"Big C" is a traditional University of California, Berkeley fight song closely associated with the California Golden Bears football program and campus spirit.
-
B.
Big G
Big G is the costumed mascot of the Harlem Globetrotters, known for entertaining crowds with comedic antics and fan interaction during the team’s exhibition basketball games.
-
C.
Big J
Big J is the affectionate nickname for the USS New Jersey (BB-62), a famed Iowa-class battleship now preserved as a museum and memorial.
-
D.
Bigi
Bigi is the youngest son of Michael Jackson, originally nicknamed "Blanket," who later chose to go by the name Bigi.
-
E.
Buy n Large
Buy n Large is the massive, monopolistic megacorporation in Pixar's "WALL·E" universe that dominates global commerce and spacefaring operations.
- 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_69d86dada3808190825d5f80d72fbe88 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1833da68881908710fb2c28e8c6d0 |
completed | April 17, 2026, 12:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffdbd3a1248190ad055892cebde5f0 |
completed | May 10, 2026, 1:13 a.m. |
Created at: April 10, 2026, 4:56 a.m.