Triple
T17431221
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luras |
E423873
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Arzachena |
—
|
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: Arzachena | Statement: [Luras, locatedNear, Arzachena]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arzachena Context triple: [Luras, locatedNear, Arzachena]
-
A.
Arzachena
chosen
Arzachena is a town in northeastern Sardinia, Italy, known for its archaeological sites and proximity to the Costa Smeralda resort area.
-
B.
Aracena
Aracena is a historic town in southwestern Spain renowned for its medieval castle and the Gruta de las Maravillas cave system.
-
C.
Santurtzi
Santurtzi is a coastal town and municipality in the Greater Bilbao area of northern Spain, known for its fishing port and maritime traditions.
-
D.
Orduña
Orduña is a historic town in the Basque Country of northern Spain, known for its medieval heritage and strategic location along traditional trade routes.
-
E.
Aizkorri
Aizkorri is a prominent mountain massif in the Basque Country of northern Spain, known for its rugged limestone peaks and popular hiking routes.
- 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_69d889d88b6081908bada047f5b3ba51 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4490072b48190a39b1ac7bb5eb035 |
completed | April 19, 2026, 3:16 a.m. |
Created at: April 10, 2026, 5:46 a.m.