Triple
T16060096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Móra d’Ebre |
E389584
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Ginestar |
E389588
|
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: Ginestar | Statement: [Móra d’Ebre, borderedBy, Ginestar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ginestar Context triple: [Móra d’Ebre, borderedBy, Ginestar]
-
A.
Ginestar
chosen
Ginestar is a small village in Catalonia, Spain, known for its agricultural landscape along the Ebro River.
-
B.
Gerinish
Gerinish is a small crofting settlement on South Uist in the Outer Hebrides of Scotland.
-
C.
Gimonde
Gimonde is a rural civil parish in the municipality of Bragança in northeastern Portugal, known for its traditional architecture and natural landscapes.
-
D.
Ginir
Ginir is a town in Ethiopia’s Oromia Region, serving as an administrative and commercial center within the Bale Zone.
-
E.
Alidoro
Alidoro is the wise philosopher and tutor to Prince Ramiro in Rossini’s opera "La Cenerentola," who secretly guides and protects Cinderella.
- 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_69d86dae698881908327ef2d67706cb9 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1837850288190910ef37d6484c600 |
completed | April 17, 2026, 12:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffdbe88a608190bc0a0cbfdb71e81d |
completed | May 10, 2026, 1:14 a.m. |
Created at: April 10, 2026, 4:57 a.m.