Triple
T222171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American League Championship Series |
E4237
|
entity |
| Predicate | hasGameType |
P8300
|
FINISHED |
| Object | postseason game |
—
|
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: postseason game | Statement: [American League Championship Series, hasGameType, postseason game]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGameType Context triple: [American League Championship Series, hasGameType, postseason game]
-
A.
notableGameType
Indicates that a game is of a particular type or category for which the subject is especially well known or notable.
-
B.
hasServiceType
Indicates that an entity is associated with or categorized by a particular type of service.
-
C.
hasDeckType
Indicates that an entity possesses or is associated with a specific type or category of deck.
-
D.
hasScoreboardType
Indicates the specific kind or category of scoreboard associated with an entity.
-
E.
hasPlatformType
Indicates that an entity is associated with or characterized by a specific type or category of platform.
- 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_69a2573508588190b522c2476d91acfe |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25c705fd88190bfee7f5e1f7cee17 |
completed | Feb. 28, 2026, 3:09 a.m. |
| PD | Predicate disambiguation | batch_69a25b5617788190814358aee3f7ae37 |
completed | Feb. 28, 2026, 3:04 a.m. |
| PDg | Predicate description generation | batch_69a25c2bda788190bcfc0bc94686f9e0 |
completed | Feb. 28, 2026, 3:08 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.