Triple
T34833050
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South of the Border, South Carolina |
E1004117
|
entity |
| Predicate | hasOnsiteLodging |
P181081
|
FINISHED |
| Object | South of the Border Motor Inn |
—
|
NE NERFINISHED |
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: South of the Border Motor Inn | Statement: [South of the Border, South Carolina, hasOnsiteLodging, South of the Border Motor Inn]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOnsiteLodging Context triple: [South of the Border, South Carolina, hasOnsiteLodging, South of the Border Motor Inn]
-
A.
hasNoLodgingOnSite
Indicates that no lodging or accommodation facilities are available at the specified location or site.
-
B.
hasAccommodation
Indicates that an entity provides, owns, or is associated with a place for someone to stay or live.
-
C.
hasDayLodge
Indicates that a location or facility includes or is associated with a day-use lodge building or area.
-
D.
hasHotelsOnSite
Indicates that the subject location includes one or more hotels situated directly on its premises.
-
E.
hasAccommodations
chosen
Indicates that one entity provides, contains, or offers lodging, facilities, or special arrangements for another entity.
- 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_69f76db7d1b4819093bd4912d80d845d |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fbc36ce1f88190a7fa1656b714e107 |
completed | May 6, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69fbbd13595c81908719f52c3d37a7e8 |
completed | May 6, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4 p.m.