Triple
T13967554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pampa de La Quinua |
E335963
|
entity |
| Predicate | nearbyCulturalAttraction |
P90437
|
FINISHED |
| Object | town of Quinua known for traditional ceramics |
—
|
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: town of Quinua known for traditional ceramics | Statement: [Pampa de La Quinua, nearbyCulturalAttraction, town of Quinua known for traditional ceramics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyCulturalAttraction Context triple: [Pampa de La Quinua, nearbyCulturalAttraction, town of Quinua known for traditional ceramics]
-
A.
nearbyVenue
Indicates that one venue is located close to another venue in physical space.
-
B.
typicalNearbyLandmarks
chosen
Indicates that certain landmarks are commonly found in the vicinity of a given place or location.
-
C.
hasNearbyCulturalDistrict
Indicates that an entity is located close to a designated cultural district or area with concentrated cultural activities.
-
D.
nearbyLocation
Indicates that one location is situated close to another location in physical space.
-
E.
nearbyUrbanCenter
Indicates that one location is geographically close to an urban center, such as a city or large town.
- 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_69d81c61f3508190aaf2ca0dc0002c59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e8c9e988190a84c9ca8a78b515f |
completed | April 14, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69dd465a21408190b912a42c50ffa0d9 |
completed | April 13, 2026, 7:39 p.m. |
Created at: April 9, 2026, 10:18 p.m.