Triple
T12819349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marloes Peninsula |
E306486
|
entity |
| Predicate | hasNearbySettlement |
P4647
|
FINISHED |
| Object | Marloes |
E1004357
|
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: Marloes | Statement: [Marloes Peninsula, hasNearbySettlement, Marloes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marloes Context triple: [Marloes Peninsula, hasNearbySettlement, Marloes]
-
A.
Marloes
chosen
Marloes is a coastal village in Pembrokeshire, Wales, known for its dramatic cliffs, nearby islands rich in wildlife, and scenic seaside landscapes.
-
B.
Saskia
Saskia is a female given name of Germanic origin, most famously borne by Saskia van Uylenburgh, the wife and frequent model of the Dutch painter Rembrandt.
-
C.
Marike
Marike is a feminine given name of Dutch and Afrikaans origin, commonly used in the Netherlands and South Africa.
-
D.
Jolanda
Jolanda is a feminine given name, commonly considered a variant of Yolanda, used in various European countries.
-
E.
Marlies
Marlies is the common nickname for the Toronto Marlboros, a historic Canadian junior ice hockey team based in Toronto.
- 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_69d7bdf46c448190b1faa55aaacb6317 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e9e5a2481908921d097df541db8 |
completed | April 10, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f69b97ffd481909c540f52c781f63f |
completed | May 3, 2026, 12:49 a.m. |
Created at: April 9, 2026, 5:31 p.m.