Triple
T36026822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heater |
E1042153
|
entity |
| Predicate | entertainsDuring |
P185999
|
FINISHED |
| Object | in-game promotions |
—
|
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: in-game promotions | Statement: [Heater, entertainsDuring, in-game promotions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: entertainsDuring Context triple: [Heater, entertainsDuring, in-game promotions]
-
A.
isEntertainer
Indicates that one entity works in entertainment, performing or creating content to amuse or engage an audience.
-
B.
entertainedTroopsDuring
Indicates that an entity provided entertainment or performances for military troops during a specified time period or event.
-
C.
entertainmentType
Indicates the kind or category of entertainment associated with an entity or event.
-
D.
entertainmentFocus
Indicates that one entity is primarily concerned with, directed toward, or centered on providing or engaging in entertainment for another entity or context.
-
E.
hasQueueEntertainment
Indicates that an entity provides or features entertainment specifically for people waiting in a queue.
- 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_69f76e2c568881909e1e21f85252b0f0 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7c83f5960819089610ed39c839678 |
completed | May 3, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69f7c475c58c8190a883554231e88c88 |
completed | May 3, 2026, 9:56 p.m. |
| PDg | Predicate description generation | batch_69f7c776b4088190bef550c869da530d |
completed | May 3, 2026, 10:08 p.m. |
Created at: May 3, 2026, 4:07 p.m.