Triple
T10402078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hank Bauer |
E245171
|
entity |
| Predicate | managerialRecordLosses |
P53085
|
FINISHED |
| Object | 544 (MLB career) |
—
|
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: 544 (MLB career) | Statement: [Hank Bauer, managerialRecordLosses, 544 (MLB career)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: managerialRecordLosses Context triple: [Hank Bauer, managerialRecordLosses, 544 (MLB career)]
-
A.
seasonRecordLosses
Indicates the number of games a team lost during a specific season.
-
B.
careerLosses
Indicates the total number of defeats or losses an entity has accumulated over the course of its entire career.
-
C.
careerWinLossRecord
Indicates the overall tally of wins and losses an entity has accumulated over the entire span of its career.
-
D.
regularSeasonLosses
Indicates the number of games a team lost during the regular season portion of a competition or league.
-
E.
managerialLossesMLB
chosen
Indicates the number of games a manager has lost while managing a Major League Baseball team.
- 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_69d381be340c8190b05998703d42d224 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9e42da08190a5383df3df6d3c18 |
completed | April 7, 2026, 11:26 a.m. |
| PD | Predicate disambiguation | batch_69d4dfb438c481908dff87c47de2f069 |
completed | April 7, 2026, 10:43 a.m. |
Created at: April 6, 2026, 12:08 p.m.