Triple
T101964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American League |
E2057
|
entity |
| Predicate | playsForTitle |
P6404
|
FINISHED |
| Object | American League pennant |
—
|
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: American League pennant | Statement: [American League, playsForTitle, American League pennant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: playsForTitle Context triple: [American League, playsForTitle, American League pennant]
-
A.
playedFor
Indicates that one entity has been a member of or participated as a player for a particular team, organization, or group.
-
B.
hasSportsTeam
Indicates that an entity possesses, sponsors, or is represented by a sports team.
-
C.
containsSportsTeam
Indicates that one entity (typically a location or organization) has a sports team as part of it or within its boundaries.
-
D.
teamPlayedFor
Indicates that a person was a member of and played for a particular sports team.
-
E.
notablePlayerTeam1
Indicates that the referenced player is a notable or prominent member of the first team in a given context or matchup.
- F. None of above. chosen
Provenance (4 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_69a24e0a5b7c81908d52da08c60dabc4 |
completed | Feb. 28, 2026, 2:08 a.m. |
| NER | Named-entity recognition | batch_69a25760af348190bf402089c240887d |
completed | Feb. 28, 2026, 2:48 a.m. |
| PD | Predicate disambiguation | batch_69a2563921f8819087f720b1c803579f |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2575d8a648190ad8e10d4b04e5e07 |
completed | Feb. 28, 2026, 2:47 a.m. |
Created at: Feb. 28, 2026, 2:12 a.m.