Triple
T537983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Smoky Joe Wood |
E12368
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object | Smoky Joe |
E12368
|
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: Smoky Joe | Statement: [Smoky Joe Wood, nickname, Smoky Joe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Smoky Joe Context triple: [Smoky Joe Wood, nickname, Smoky Joe]
-
A.
Smokey
Smokey is the bluetick coonhound dog who serves as the live mascot for the University of Tennessee Volunteers athletic teams.
-
B.
Smoky Joe Wood
chosen
Smoky Joe Wood was an American Major League Baseball pitcher renowned for his dominant fastball and standout performances for the Boston Red Sox in the early 1910s.
-
C.
Willie
Willie is the first name of Willie Nelson, the iconic American country music singer-songwriter and cultural figure.
-
D.
Hippo Vaughn
Hippo Vaughn was an early 20th-century Major League Baseball pitcher best known for his standout seasons with the Chicago Cubs, including a key role in their 1918 pennant-winning campaign.
-
E.
Laffing Sal
Laffing Sal is a historic, animatronic laughing woman figure from early 20th-century amusement parks, now preserved as a popular attraction at San Francisco’s Musée Mécanique.
- 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_69a4933208e88190891f5debab1b776d |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a496dc0aac8190afb75ec6c47a1d2d |
completed | March 1, 2026, 7:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4c66fa348819081e004fb4350f4ea |
completed | March 1, 2026, 11:06 p.m. |
Created at: March 1, 2026, 7:32 p.m.