Triple
T438419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Babe Ruth |
E10060
|
entity |
| Predicate | battingAverageCareer |
P7538
|
FINISHED |
| Object | .342 |
—
|
LITERAL 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: .342 | Statement: [Babe Ruth, battingAverageCareer, .342]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: battingAverageCareer Context triple: [Babe Ruth, battingAverageCareer, .342]
-
A.
careerBattingAverage
chosen
Indicates the long-term batting performance of a player, calculated as their total hits divided by total at-bats over their entire career.
-
B.
careerOnBasePercentage
Indicates a player's on-base percentage averaged over the entire duration of their career.
-
C.
careerSluggingPercentage
Indicates the overall slugging percentage a player has achieved across their entire career.
-
D.
careerRBIs
Indicates the total number of runs a player has batted in over the course of their entire career.
-
E.
careerEarnedRunAverage
Indicates the average number of earned runs a pitcher allows per nine innings over the entire span of their career.
- F. None of above.
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_69a2e8465ef481909655c681b01e2986 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2ef283be881909444aaf257451747 |
completed | Feb. 28, 2026, 1:35 p.m. |
| PD | Predicate disambiguation | batch_69a2eddb98e081909efcf9f0a955a908 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.