Triple
T6826098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Orotava |
E157018
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Adeje |
E173112
|
NE 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: Adeje | Statement: [La Orotava, borders, Adeje]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Adeje Context triple: [La Orotava, borders, Adeje]
-
A.
Adeje
chosen
Adeje is a coastal municipality and popular tourist destination in the southwest of Tenerife in Spain’s Canary Islands.
-
B.
Hāna
Hāna is a small, remote town on the eastern coast of Maui, Hawaii, known for its lush landscapes, scenic coastal views, and the famously winding Road to Hāna.
-
C.
Anaga
Anaga is a rugged, mountainous district in northeastern Tenerife known for its ancient laurel forests, dramatic coastal landscapes, and traditional rural villages.
-
D.
Tafuna
Tafuna is a major suburban and commercial area on the island of Tutuila in American Samoa, known for its population density and proximity to the territory’s main airport.
-
E.
Kapalua
Kapalua is a resort community on the northwest coast of Maui, Hawaii, known for its luxury accommodations, golf courses, and scenic beaches.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c6882a5b5c8190917a7db9ed36bad1 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d58375248190935dd38d618994e3 |
completed | March 27, 2026, 7:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c723f12a148190adbb05782a2041b6 |
completed | March 28, 2026, 12:42 a.m. |
Created at: March 27, 2026, 2:18 p.m.