Triple
T15187859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MYK |
E362923
|
entity |
| Predicate | associatedWithCity |
P1481
|
FINISHED |
| Object | Mayen |
E761535
|
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: Mayen | Statement: [MYK, associatedWithCity, Mayen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mayen Context triple: [MYK, associatedWithCity, Mayen]
-
A.
Mayen
chosen
Mayen is a surname most notably borne by Dutch seafarer and explorer Jan Jacobszoon Mayen, after whom the Arctic island of Jan Mayen is named.
-
B.
Senja
Senja is Norway’s second-largest island, renowned for its dramatic coastal mountains, fishing villages, and scenic Arctic landscapes.
-
C.
Steinsel
Steinsel is a small commune and town in central Luxembourg, situated just north of the capital city.
-
D.
Lonsee
Lonsee is a small municipality in the Alb-Donau district of Baden-Württemberg, Germany, situated on the Swabian Jura near the city of Ulm.
-
E.
Maasin
Maasin is a coastal city in the Philippines that serves as the administrative, economic, and religious center of the province of Southern Leyte.
- 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_69d85a09a39c81908759f23268e2d408 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0067995fc8190b048f15086bd42f0 |
completed | April 15, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fedd2a2eb48190a569847d2f583c61 |
completed | May 9, 2026, 7:07 a.m. |
Created at: April 10, 2026, 3:09 a.m.