Triple
T32826146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Puente de Dios |
E839559
|
entity |
| Predicate | nearOtherAttraction |
P61270
|
FINISHED |
| Object | Cascadas de Tamasopo |
—
|
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: Cascadas de Tamasopo | Statement: [Puente de Dios, nearOtherAttraction, Cascadas de Tamasopo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearOtherAttraction Context triple: [Puente de Dios, nearOtherAttraction, Cascadas de Tamasopo]
-
A.
nearestTouristDestination
Indicates that one location is the closest tourist destination to another specified location.
-
B.
nearbyLocation
chosen
Indicates that one location is situated close to another location in physical space.
-
C.
nearbyVenue
Indicates that one venue is located close to another venue in physical space.
-
D.
hasAttractionNearby
Indicates that one entity is located close to another entity that serves as an attraction or point of interest.
-
E.
typicalNearbyLandmarks
Indicates that certain landmarks are commonly found in the vicinity of a given place or location.
- 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_69f3493f22f88190ae6dd4bc15b6cf8d |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d16f5cb881908eed141afaaa0b51 |
completed | May 3, 2026, 4:39 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe45554819089cbbd538d992132 |
completed | May 3, 2026, 4:32 a.m. |
Created at: May 1, 2026, 1:15 a.m.