Triple
T3741577
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oak Park Mall |
E79710
|
entity |
| Predicate | hasEntertainmentOptions |
P51190
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Oak Park Mall, hasEntertainmentOptions, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEntertainmentOptions Context triple: [Oak Park Mall, hasEntertainmentOptions, yes]
-
A.
hasEntertainmentVenue
Indicates that an entity possesses, contains, or is associated with an entertainment venue as part of its facilities or offerings.
-
B.
hasQueueEntertainment
Indicates that an entity provides or features entertainment specifically for people waiting in a queue.
-
C.
hasSpectatorAmenities
Indicates that a place or facility provides amenities or features intended for the comfort or convenience of spectators.
-
D.
hasConcessions
Indicates that one entity provides or contains concession facilities, services, or rights (such as food, drink, or merchandise sales) for another entity or within a given context.
-
E.
hasAdultPrograms
Indicates that an entity offers or is associated with programs or services specifically designed for adults.
- 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_69ad8b115610819095b02007da5ca3cb |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb549490819084ebe69aae5ccf95 |
completed | March 8, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69adc048f28c819092bed16a95a3cac1 |
completed | March 8, 2026, 6:30 p.m. |
| PDg | Predicate description generation | batch_69adc198b95481908ca6e4e875aae446 |
completed | March 8, 2026, 6:36 p.m. |
Created at: March 8, 2026, 3:34 p.m.