Triple
T14646482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arles railway station |
E343863
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Sète |
E157839
|
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: Sète | Statement: [Arles railway station, connectsTo, Sète]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sète Context triple: [Arles railway station, connectsTo, Sète]
-
A.
Sète
chosen
Sète is a coastal port city in southern France known for its canals, fishing industry, and vibrant maritime culture on the Mediterranean Sea.
-
B.
Marseillan
Marseillan is a coastal commune in southern France known for its historic port, oyster farming, and proximity to the Étang de Thau lagoon.
-
C.
La Grande-Motte
La Grande-Motte is a seaside resort town on France’s Mediterranean coast, noted for its distinctive modernist pyramid-shaped architecture and beaches.
-
D.
Perpignan
Perpignan is a historic city in southern France near the Spanish border, known for its Catalan culture and Mediterranean climate.
-
E.
Béziers
Béziers is a historic city in southern France known for its wine production, ancient Roman heritage, and the famous Feria de Béziers festival.
- 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_69d822e1a2cc81908e5bb93cf61ce3cc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb4ebe8048190a2935d00c9cfd8be |
completed | April 14, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe6b40633481909882645f73d3e2c6 |
completed | May 8, 2026, 11:01 p.m. |
Created at: April 10, 2026, 1:26 a.m.