Triple
T14537926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Babe Siebert |
E341097
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object | Babe |
E694964
|
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: Babe | Statement: [Babe Siebert, nickname, Babe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Babe Context triple: [Babe Siebert, nickname, Babe]
-
A.
Babe
Babe is the famous nickname of George Herman "Babe" Ruth, the legendary American baseball player widely regarded as one of the greatest hitters in the sport's history.
-
B.
Babe
Babe is a critically acclaimed 1995 family film that blends live-action and animatronics to tell the story of a pig who aspires to be a sheepdog.
-
C.
Babe
"Babe" is a novel by American author Marianne Wiggins, known for its inventive narrative voice and exploration of complex personal relationships.
-
D.
Babe
chosen
Babe is the nickname of Babe Phelps, an American Major League Baseball catcher active in the 1930s and early 1940s.
-
E.
Babe
Babe is the nickname of Thomas "Babe" Levy, the fictional graduate student and marathon runner portrayed by Dustin Hoffman in the 1976 thriller film "Marathon Man."
- 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_69d822dac79c8190a84a073f3cbaced5 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb1bb90008190947ac0961393446d |
completed | April 14, 2026, 9:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd7a5ae04881909e7eb766fca33066 |
completed | May 8, 2026, 5:53 a.m. |
Created at: April 10, 2026, 1:22 a.m.