Triple
T12112910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bo Schembechler |
E288477
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object | Bo |
E288477
|
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: Bo | Statement: [Bo Schembechler, nickname, Bo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bo Context triple: [Bo Schembechler, nickname, Bo]
-
A.
Bo
Bo was an extinct indigenous language of the Great Andamanese people, once spoken in the Andaman Islands of India.
-
B.
Bo
Bo was the Portuguese Water Dog who served as one of the Obama family's beloved First Pets during Barack Obama's presidency.
-
C.
Bo
chosen
Bo is the widely known nickname of legendary American college football coach Bo Schembechler, famed for his long tenure at the University of Michigan.
-
D.
Bo
Bo is a masculine given name commonly used in Scandinavian countries and parts of Europe.
-
E.
Bo
Bo was the early capital city of the Shang dynasty in ancient China, serving as a major political and cultural center.
- 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_69d6ab4a5c448190a110d1273314b21a |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9156814148190b47d63a89fcab17c |
completed | April 10, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60a75f77881908345a585a689f69f |
completed | May 2, 2026, 2:30 p.m. |
Created at: April 8, 2026, 9:49 p.m.