Triple
T10132172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Holland |
E226364
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Spijkenisse |
E70497
|
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: Spijkenisse | Statement: [South Holland, containsCity, Spijkenisse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Spijkenisse Context triple: [South Holland, containsCity, Spijkenisse]
-
A.
Spijkenisse
chosen
Spijkenisse is a town and former municipality in the western Netherlands, now part of the municipality of Nissewaard and known as a suburban area near Rotterdam.
-
B.
Sparnacien
Sparnacien is the French demonym for an inhabitant of the town of Épernay in the Champagne region.
-
C.
Winkel van Sinkel
Winkel van Sinkel is a historic former department store and cultural landmark in the center of Utrecht, Netherlands, now used as a venue for events, dining, and nightlife.
-
D.
Spicheren
Spicheren is a commune in northeastern France near the German border, historically notable as the site of a major battle in the Franco-Prussian War.
-
E.
Zesgehuchten
Zesgehuchten was a former village and municipality in the Dutch province of North Brabant, now part of the city of Geldrop-Mierlo.
- 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_69ca843057b48190a86730167f5d6b98 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cdd336cbf48190b647c69675d0b06f |
completed | April 2, 2026, 2:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2e5ce3fcc8190b1d07dbba34d6bff |
completed | April 5, 2026, 10:44 p.m. |
Created at: March 30, 2026, 9:06 p.m.