Triple
T2642339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tunes railway station |
E62898
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Faro |
E84088
|
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: Faro | Statement: [Tunes railway station, connectsTo, Faro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Faro Context triple: [Tunes railway station, connectsTo, Faro]
-
A.
Faro
chosen
Faro is a historic coastal city in southern Portugal that serves as the capital of the Algarve region and a major gateway for tourism.
-
B.
Hafnarfjörður
Hafnarfjörður is a port town in southwestern Iceland known for its lava-field setting, fishing industry, and role as part of the Reykjavík metropolitan area.
-
C.
Dokkum
Dokkum is a historic fortified town in the northern Netherlands, known as one of the Frisian Eleven Cities and for its association with the martyrdom of Saint Boniface.
-
D.
Køpmannæhafn
Køpmannæhafn is the historical Danish name for the city now known as Copenhagen, reflecting its origins as a merchant harbor.
-
E.
Lenakel
Lenakel is an Oceanic language spoken primarily on Tanna Island in Vanuatu.
- 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_69ab4c3f2dcc819082df80f5e032f690 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abd8ff34988190ba9d69ce9d77c71d |
completed | March 7, 2026, 7:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afa04f0d448190adf113831fb5bc42 |
completed | March 10, 2026, 4:38 a.m. |
Created at: March 6, 2026, 9:53 p.m.