Triple
T2811246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American Tobacco Campus |
E54174
|
entity |
| Predicate | hasEntertainmentVenues |
P23473
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [American Tobacco Campus, hasEntertainmentVenues, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEntertainmentVenues Context triple: [American Tobacco Campus, hasEntertainmentVenues, true]
-
A.
hasEntertainmentVenue
chosen
Indicates that an entity possesses, contains, or is associated with an entertainment venue as part of its facilities or offerings.
-
B.
typicalVenues
Indicates that the specified locations are common or standard places where the associated activity, event, or entity usually occurs or is hosted.
-
C.
hasNightlifeArea
Indicates that a place contains or is associated with an area characterized by nightlife activities such as bars, clubs, or evening entertainment venues.
-
D.
hasLiveMusic
Indicates that a place or event features live musical performances as part of its offerings.
-
E.
hasRecreationalOrganization
Indicates that an entity is associated with, or hosts, a recreational organization such as a club, team, or leisure group.
- 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_69ab49dcee188190b5c6eca9ae9e3469 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abde354a5881908cd3d545f7dda81c |
completed | March 7, 2026, 8:13 a.m. |
| PD | Predicate disambiguation | batch_69abdd0740208190911dc9c9546a79ae |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:59 p.m.