Triple
T37551996
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gamescom 2015 |
E933609
|
entity |
| Predicate | hasEntertainmentArea |
P51190
|
FINISHED |
| Object | general public |
—
|
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: general public | Statement: [Gamescom 2015, hasEntertainmentArea, general public]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEntertainmentArea Context triple: [Gamescom 2015, hasEntertainmentArea, general public]
-
A.
hasEntertainmentVenue
Indicates that an entity possesses, contains, or is associated with an entertainment venue as part of its facilities or offerings.
-
B.
hasEntertainmentOptions
chosen
Indicates that an entity provides or includes one or more forms of entertainment or leisure activities as options.
-
C.
isEntertainmentDistrict
Indicates that a location functions primarily as an area dedicated to entertainment activities, venues, and nightlife.
-
D.
hasQueueEntertainment
Indicates that an entity provides or features entertainment specifically for people waiting in a queue.
-
E.
hasNearbyEntertainmentDistrict
Indicates that one location is situated close enough to another area known for entertainment venues (such as bars, theaters, or nightlife) to be considered nearby.
- 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_69f76eca55bc8190acf25741793d5dac |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fe12a899d4819080d48423f32eace9 |
completed | May 8, 2026, 4:43 p.m. |
| PD | Predicate disambiguation | batch_69fe0d7f6aa08190a1d2dfc025d4e0dc |
completed | May 8, 2026, 4:21 p.m. |
Created at: May 3, 2026, 4:17 p.m.