Triple
T15575629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American League pennant 1908 |
E374361
|
entity |
| Predicate | teamRegularSeasonRecordLosses |
P14874
|
FINISHED |
| Object | 63 |
—
|
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: 63 | Statement: [American League pennant 1908, teamRegularSeasonRecordLosses, 63]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teamRegularSeasonRecordLosses Context triple: [American League pennant 1908, teamRegularSeasonRecordLosses, 63]
-
A.
regularSeasonLosses
chosen
Indicates the number of games a team lost during the regular season portion of a competition or league.
-
B.
seasonRecordLosses
Indicates the number of games a team lost during a specific season.
-
C.
awayTeamRegularSeasonRecord
Indicates the win-loss (and possibly tie) record that the away team has accumulated during the regular season.
-
D.
losingTeamRegularSeasonRecord
Indicates the win-loss record that the losing team had during the regular season.
-
E.
coachingRecordNFLRegularSeasonLosses
Indicates the number of games a coach has lost in NFL regular season play.
- 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_69d85ccd575081908909b71a3f3e3a61 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e2140388190a8df7b835eaa72ce |
completed | April 16, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69deda7e6e748190b29ccce23298afef |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:10 a.m.