Triple
T12883188
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ermesinde railway station |
E308154
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Ermesinde |
E1009593
|
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: Ermesinde | Statement: [Ermesinde railway station, serves, Ermesinde]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ermesinde Context triple: [Ermesinde railway station, serves, Ermesinde]
-
A.
Ermesinde
chosen
Ermesinde is a town in northern Portugal, near Porto, known as a residential and transport hub within the Porto metropolitan area.
-
B.
Alidoro
Alidoro is the wise philosopher and tutor to Prince Ramiro in Rossini’s opera "La Cenerentola," who secretly guides and protects Cinderella.
-
C.
Halistra
Halistra is a small crofting settlement on the Waternish peninsula of the Isle of Skye in Scotland.
-
D.
Lucciana
Lucciana is a commune in the Haute-Corse department of Corsica, France, known for hosting Bastia – Poretta Airport and its proximity to the island’s northeastern coast.
-
E.
Mora
Mora is a town in central Sweden’s Dalarna region, known for its traditional Swedish culture, proximity to Lake Siljan, and as the finish line of the Vasaloppet cross-country ski race.
- 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_69d7bdf69bc48190af6c2621f28ca351 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d970fd15888190baf90fc30f2a3e25 |
completed | April 10, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6af55623081909fd171129f439302 |
completed | May 3, 2026, 2:13 a.m. |
Created at: April 9, 2026, 5:39 p.m.