Triple
T15579318
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Co-Star Mode |
E374450
|
entity |
| Predicate | affectsDifficulty |
P100819
|
FINISHED |
| Object | can make game easier |
—
|
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: can make game easier | Statement: [Co-Star Mode, affectsDifficulty, can make game easier]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: affectsDifficulty Context triple: [Co-Star Mode, affectsDifficulty, can make game easier]
-
A.
hasDifficultyEffect
chosen
Indicates that one entity causes a change in the difficulty level or challenge associated with another entity or activity.
-
B.
difficulty
Indicates the level of challenge, complexity, or effort required to perform an action, solve a problem, or achieve a particular outcome.
-
C.
difficultyRelativeTo
Indicates that one entity’s level of difficulty is being compared to and expressed in relation to another entity’s level of difficulty.
-
D.
difficultySource
Indicates that one entity is the cause, origin, or contributing factor to the difficulty or challenge experienced in relation to another entity or situation.
-
E.
affectedLevel
Indicates the degree or extent to which one entity is impacted or influenced by another entity or event.
- 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_69e04e24064c8190b132c3092877fbfa |
completed | April 16, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69deda817e9881909b0c66fc9056f7d5 |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:11 a.m.