Triple
T20030902
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tanjung Tinggi Beach |
E495120
|
entity |
| Predicate | hasAccommodationTypeNearby |
P115275
|
FINISHED |
| Object | beachfront 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: beachfront hotels | Statement: [Tanjung Tinggi Beach, hasAccommodationTypeNearby, beachfront hotels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAccommodationTypeNearby Context triple: [Tanjung Tinggi Beach, hasAccommodationTypeNearby, beachfront hotels]
-
A.
hasNearbyLodge
Indicates that one entity is located close to or in the vicinity of a lodge associated with another entity.
-
B.
hasNearbyHotel
Indicates that one entity is located close to or within a short distance of a hotel.
-
C.
hasNearbyPropertyType
chosen
Indicates that one entity has another entity of a specified property type located in close physical proximity to it.
-
D.
hasNearbyHotelCluster
Indicates that one or more hotels are located in close proximity to the referenced place or area, forming a spatial cluster.
-
E.
nearbyResortArea
Indicates that a resort area is located close to or within a short distance of a specified place or 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_69da626bfd288190aa5d65098b6433ae |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66291a00c8190b0b895909f32d623 |
completed | April 20, 2026, 5:29 p.m. |
| PD | Predicate disambiguation | batch_69e54ce752748190a0a1ffddd0372271 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:36 p.m.