Triple
T22393584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franco-British Exhibition 1908 |
E553571
|
entity |
| Predicate | hadEntertainment |
P51190
|
FINISHED |
| Object | funfair attractions |
—
|
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: funfair attractions | Statement: [Franco-British Exhibition 1908, hadEntertainment, funfair attractions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadEntertainment Context triple: [Franco-British Exhibition 1908, hadEntertainment, funfair attractions]
-
A.
entertainmentFocus
Indicates that one entity is primarily concerned with, directed toward, or centered on providing or engaging in entertainment for another entity or context.
-
B.
hasEntertainmentOptions
chosen
Indicates that an entity provides or includes one or more forms of entertainment or leisure activities as options.
-
C.
entertainmentType
Indicates the kind or category of entertainment associated with an entity or event.
-
D.
hasQueueEntertainment
Indicates that an entity provides or features entertainment specifically for people waiting in a queue.
-
E.
hasPreMatchEntertainment
Indicates that there is entertainment or activities provided before a match or game takes place.
- 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_69e11e4cf87c8190a1ff474daec326b7 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1585ce39c819082b62e7f2e297d9b |
completed | April 29, 2026, 1:01 a.m. |
| PD | Predicate disambiguation | batch_69e73015484c8190a9a0b9f554b61a81 |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:45 p.m.