Triple
T20466478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seeham |
E502061
|
entity |
| Predicate | hasNearbyLake |
P17985
|
FINISHED |
| Object | Mattsee |
—
|
NE NERFINISHED |
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: Mattsee | Statement: [Seeham, hasNearbyLake, Mattsee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mattsee Context triple: [Seeham, hasNearbyLake, Mattsee]
-
A.
Mattsee
chosen
Mattsee is a picturesque market town in the Austrian state of Salzburg, known for its lakeside setting, historic abbey, and well-preserved medieval center.
-
B.
Meeder
Meeder is a municipality in the Bavarian region of Germany, situated within the Coburg district.
-
C.
Meent
Meent is a tram stop on Amsterdam’s Amstelveenlijn serving the residential area of Amstelveen in the Netherlands.
-
D.
Mattexey
Mattexey is a small rural commune located in the Meurthe-et-Moselle department in northeastern France.
-
E.
Saeein
Saeein is an honorific title used in Sindhi culture to show deep respect, particularly for revered figures such as the nationalist leader and intellectual G. M. Syed.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4ae5f1081908768b0c9a3a0bf38 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e696aa0794819082c9989b1f7e9f37 |
completed | April 20, 2026, 9:12 p.m. |
Created at: April 16, 2026, 11:33 a.m.