Triple
T16060653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Móra la Nova railway station |
E389601
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Móra la Nova |
E1191079
|
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: Móra la Nova | Statement: [Móra la Nova railway station, locatedIn, Móra la Nova]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Móra la Nova Context triple: [Móra la Nova railway station, locatedIn, Móra la Nova]
-
A.
Móra la Nova
chosen
Móra la Nova is a municipality in Catalonia, Spain, situated on the right bank of the Ebro River in the Ribera d'Ebre comarca.
-
B.
Maiao
Maiao is a small, sparsely populated island in French Polynesia’s Society Islands, known for its traditional Polynesian lifestyle and limited accessibility.
-
C.
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.
-
D.
Mora
Mora is a canton in Costa Rica’s San José Province known for its rural landscapes, agricultural activities, and small-town communities.
-
E.
Mora
Mora is a surname of Hungarian origin most notably borne by the German-Hungarian writer Terézia Mora.
- 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_69ffeb8b1b2c8190949943b20f2f8574 |
completed | May 10, 2026, 2:20 a.m. |
Created at: April 10, 2026, 4:57 a.m.