Triple
T10534191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tanger Outlets Sevierville |
E248519
|
entity |
| Predicate | hasPublicRestrooms |
P1976
|
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: [Tanger Outlets Sevierville, hasPublicRestrooms, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPublicRestrooms Context triple: [Tanger Outlets Sevierville, hasPublicRestrooms, yes]
-
A.
hasRestrooms
chosen
Indicates that a place or facility provides access to restroom or toilet amenities.
-
B.
hasNumberOfPublicBathhouses
Indicates the quantity of public bathhouses associated with a given entity.
-
C.
hasPublicSpaces
Indicates that an entity includes or provides areas that are accessible and usable by the general public.
-
D.
hasAblutionFacilities
Indicates that an entity provides or is equipped with facilities for performing ablution or ritual washing.
-
E.
hasPublicHouse
Indicates that one entity possesses, operates, or is associated with a public house (such as a bar or pub) as part of its facilities or holdings.
- 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_69d381c5c7448190bec34bee7ec72bac |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d50a1a754c8190b53f2df28a1dfef1 |
completed | April 7, 2026, 1:43 p.m. |
| PD | Predicate disambiguation | batch_69d4fb9729288190a0149f127acd7ae3 |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:31 p.m.