Triple
T24734638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1994 Major League Baseball season |
E618376
|
entity |
| Predicate | gamesPlayedPerTeamRange |
P114326
|
FINISHED |
| Object | 112–117 |
—
|
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: 112–117 | Statement: [1994 Major League Baseball season, gamesPlayedPerTeamRange, 112–117]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gamesPlayedPerTeamRange Context triple: [1994 Major League Baseball season, gamesPlayedPerTeamRange, 112–117]
-
A.
gamesPerTeamActuallyPlayedRange
chosen
Indicates the range of games that each team has actually played, as opposed to scheduled or expected games.
-
B.
typicalNumberOfGamesRange
Indicates the usual minimum and maximum number of games typically played in the associated context or setting.
-
C.
gameCountPerTeam
Indicates the number of games associated with or played by each team.
-
D.
conferenceGamesPerTeam
Indicates the number of games each team plays against opponents within its conference.
-
E.
teamCountPerGame
Indicates the number of teams that participate in a single game or match.
- 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_69e2fab772608190b74163751047ff50 |
completed | April 18, 2026, 3:29 a.m. |
| NER | Named-entity recognition | batch_69f422aee0408190899efe7e24ef2b40 |
completed | May 1, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69f420e92cc88190a803aecdae78a051 |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 4:03 a.m.