Triple
T1541750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MGM National Harbor |
E32882
|
entity |
| Predicate | hasSpa |
P22897
|
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: [MGM National Harbor, hasSpa, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpa Context triple: [MGM National Harbor, hasSpa, true]
-
A.
hasSpaTown
Indicates that a place is associated with or contains a town known for its spa or therapeutic bathing facilities.
-
B.
hasResortHotel
Indicates that one entity owns, includes, or is associated with a resort hotel as part of its facilities or offerings.
-
C.
hasOceanBaths
Indicates that a place or location contains or is equipped with ocean baths—man-made seawater pools or bathing facilities built along the coastline.
-
D.
hasHospitalityComponent
chosen
Indicates that something includes, involves, or is associated with a hospitality-related element, service, or function.
-
E.
hasBeach
Indicates that one entity possesses, includes, or is characterized by a beach as part of its features or environment.
- 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_69a885ed29088190a3c2d5a3d100c16e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa95c1a2948190a2b98469afec1a7d |
completed | March 6, 2026, 8:52 a.m. |
| PD | Predicate disambiguation | batch_69a907b2453c8190a41f6b88c8217d1e |
completed | March 5, 2026, 4:33 a.m. |
Created at: March 4, 2026, 7:26 p.m.