Triple
T15744807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | International Drive tourist district |
E381693
|
entity |
| Predicate | hasHotelCluster |
P96993
|
FINISHED |
| Object | resort hotels |
—
|
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: resort hotels | Statement: [International Drive tourist district, hasHotelCluster, resort hotels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHotelCluster Context triple: [International Drive tourist district, hasHotelCluster, resort hotels]
-
A.
hasNearbyHotelCluster
Indicates that one or more hotels are located in close proximity to the referenced place or area, forming a spatial cluster.
-
B.
hasResortHotel
Indicates that one entity owns, includes, or is associated with a resort hotel as part of its facilities or offerings.
-
C.
hasHotelType
Indicates that a hotel is classified as belonging to a specific type or category (e.g., resort, boutique, hostel).
-
D.
hasCluster
chosen
Indicates that one entity possesses, contains, or is associated with a specific cluster or grouping of related elements.
-
E.
isResortOf
Indicates that a location or facility functions as a resort associated with, belonging to, or serving a particular entity (such as a city, region, or organization).
- 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4d6b5788190883746ee82c799f5 |
completed | April 16, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e0052c6208819098165d61d378d13b |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:46 a.m.