Triple
T12217484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Weststellingwerf |
E291122
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object | Peperga |
E57463
|
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: Peperga | Statement: [Weststellingwerf, hasSettlement, Peperga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peperga Context triple: [Weststellingwerf, hasSettlement, Peperga]
-
A.
Peperga
chosen
Peperga is a small village in the Netherlands best known as the birthplace of Dutch colonial governor Peter Stuyvesant.
-
B.
Pêra
Pêra is a small village in Portugal’s Algarve region, known for its traditional architecture and proximity to popular coastal and tourist areas.
-
C.
Pernaja
Pernaja is a former municipality and coastal village in southern Finland, now part of the town of Loviisa.
-
D.
Peren
Peren is a town and administrative center in the northeastern Indian state of Nagaland.
-
E.
Pedasí
Pedasí is a small coastal town in Panama known for its fishing, surfing beaches, and access to nearby wildlife-rich islands on the Azuero Peninsula.
- 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_69d6ab65923081909acfc61b7a612233 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91c9419d48190b0037fe8edc681c4 |
completed | April 10, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60aa31f548190bd4f8cfe3c55614b |
completed | May 2, 2026, 2:30 p.m. |
Created at: April 8, 2026, 9:51 p.m.