Triple
T17582217
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monte Limbara |
E428230
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Berchidda |
—
|
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: Berchidda | Statement: [Monte Limbara, locatedNear, Berchidda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Berchidda Context triple: [Monte Limbara, locatedNear, Berchidda]
-
A.
Berchidda
chosen
Berchidda is a small town in the Gallura region of northern Sardinia, Italy, known for its rural character and traditional Sardinian culture.
-
B.
Turrubares
Turrubares is a rural canton in Costa Rica known for its mountainous landscapes, agricultural activities, and low population density.
-
C.
Barbeya
Barbeya is a monotypic genus of flowering plants comprising a single tree species native to arid regions of East Africa and the Arabian Peninsula.
-
D.
Basdiot
Basdiot is a coastal barangay in Moalboal, Cebu, Philippines, known for its popular beach and diving spots along the town’s tourism strip.
-
E.
Sabagreia
Sabagreia is a town located within the Kolokuma/Opokuma area of Bayelsa State in Nigeria.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889e1030481909950e140c63255b9 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e463ce8eb081909257be47d150aa04 |
completed | April 19, 2026, 5:10 a.m. |
Created at: April 10, 2026, 5:50 a.m.