Triple
T37460809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Class Challenges |
E930911
|
entity |
| Predicate | hasGameFormat |
P101458
|
FINISHED |
| Object | single-class encounter |
—
|
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: single-class encounter | Statement: [Class Challenges, hasGameFormat, single-class encounter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGameFormat Context triple: [Class Challenges, hasGameFormat, single-class encounter]
-
A.
hasPlayFormat
chosen
Indicates that something (such as a game, media, or activity) is associated with a particular format or mode in which it is played or experienced.
-
B.
hasGameType
Indicates that an entity (such as a game or match) is associated with a specific category or type of game.
-
C.
numberOfGamesFormat
Indicates the total count of distinct game formats associated with or used in a given context.
-
D.
gamesPlayedFormat
Indicates the specific format or type of game setup in which the games were played between the related entities.
-
E.
playedFormat
Indicates that an entity (such as a game, show, or media content) is or was presented, delivered, or experienced in a particular format (such as digital, physical, live, or specific media type).
- 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_69f76ec1a1148190b0a961f188d621b0 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fba68077788190b311e027435fcf87 |
completed | May 6, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69fba34c65ac8190b298f0f00d1dcc0e |
completed | May 6, 2026, 8:23 p.m. |
Created at: May 3, 2026, 4:17 p.m.