Triple
T2642380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loulé railway station |
E62899
|
entity |
| Predicate | locatedInMunicipality |
P40
|
FINISHED |
| Object | Loulé |
E67623
|
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: Loulé | Statement: [Loulé railway station, locatedInMunicipality, Loulé]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Loulé Context triple: [Loulé railway station, locatedInMunicipality, Loulé]
-
A.
Loulé
chosen
Loulé is a historic market town and municipality in southern Portugal known for its traditional architecture, lively festivals, and role as a cultural and commercial center in the Algarve region.
-
B.
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.
-
C.
Saintes-Maries-de-la-Mer
Saintes-Maries-de-la-Mer is a coastal town in southern France known as a pilgrimage site and seaside resort at the edge of the Camargue wetlands.
-
D.
Lorient
Lorient is a port city in the Brittany region of northwestern France, known for its maritime heritage and annual Interceltic Festival.
-
E.
Le Beausset
Le Beausset is a small commune in the Var department of southeastern France, near Toulon in the Provence-Alpes-Côte d'Azur region.
- 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_69afbbb328a88190b0ef889cbbe3bea3 |
completed | March 10, 2026, 6:35 a.m. |
Created at: March 6, 2026, 9:53 p.m.