Triple
T6192911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Botlektunnel |
E138437
|
entity |
| Predicate | connectsArea |
P2564
|
FINISHED |
| Object | Pernis |
E426813
|
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: Pernis | Statement: [Botlektunnel, connectsArea, Pernis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pernis Context triple: [Botlektunnel, connectsArea, Pernis]
-
A.
Pernis
chosen
Pernis is a major industrial and petrochemical area within the Port of Rotterdam, best known for hosting one of the largest oil refineries in the world.
-
B.
Perejaume
Perejaume is a contemporary Catalan artist and poet known for his conceptual explorations of landscape, language, and the relationship between art and territory.
-
C.
Pernaja
Pernaja is a former municipality and coastal village in southern Finland, now part of the town of Loviisa.
-
D.
Pereiras
Pereiras is a small locality within the municipality of Loulé in Portugal’s Algarve region.
-
E.
Gravedona
Gravedona is a picturesque town on the shores of Lake Como in northern Italy, known for its historic churches and scenic lakeside setting.
- 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_69c008ab9b3081908a11b2c744838435 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06241977c81909ab8486f5aa30be0 |
completed | March 22, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c16f1403888190b558a43998fa5d05 |
completed | March 23, 2026, 4:49 p.m. |
Created at: March 22, 2026, 4:19 p.m.