Triple
T25798641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Highway 307 |
E649753
|
entity |
| Predicate | linksTouristDestinations |
P107600
|
FINISHED |
| Object | Playa del Carmen beach area |
—
|
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: Playa del Carmen beach area | Statement: [Highway 307, linksTouristDestinations, Playa del Carmen beach area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linksTouristDestinations Context triple: [Highway 307, linksTouristDestinations, Playa del Carmen beach area]
-
A.
connectsTouristDestinations
chosen
Indicates a relationship where something links or provides a route between multiple tourist destinations.
-
B.
touristAttractionIn
Indicates that a place functions as a tourist attraction located within a specified geographic area or entity.
-
C.
relatedAttraction
Indicates that one attraction is associated with or connected to another attraction in some relevant way.
-
D.
alsoAttractsTouristsIn
Indicates that a place, in addition to another, draws or appeals to tourists within a specified location or context.
-
E.
touristGatewayTo
Indicates a relationship where one place serves as the primary access point or entry hub for tourists visiting another place.
- 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_69e7ab34f8c8819099f6c4dabdabf129 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f621fcea1481909b6f8b3af1ee6820 |
completed | May 2, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69f620dc38088190b56b2b15ed75b3c2 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 22, 2026, 6:35 a.m.