Triple
T10441169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Husum |
E246172
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Husum (historical settlement name) |
E246172
|
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: Husum (historical settlement name) | Statement: [Husum, namedAfter, Husum (historical settlement name)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Husum (historical settlement name) Context triple: [Husum, namedAfter, Husum (historical settlement name)]
-
A.
Husum
chosen
Husum is a small coastal town in northern Germany known for its North Sea harbor, maritime heritage, and role as a local cultural and commercial center.
-
B.
Biessum
Biessum is a small village in the province of Groningen in the Netherlands, now part of the municipality of Eemsdelta.
-
C.
Hodenhagen
Hodenhagen is a small municipality in Lower Saxony, Germany, known for its rural setting along the Aller River and proximity to attractions like the Serengeti Park safari zoo.
-
D.
Borssum
Borssum is a district of the seaport city of Emden in Lower Saxony, Germany, known primarily as a residential area with local amenities.
-
E.
Brinkum
Brinkum is a small municipality in the Leer district of Lower Saxony in northwestern Germany.
- 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_69d381c04fe08190957c26c526a3b05a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fb9df6fc8190830f405ef955d64b |
completed | April 7, 2026, 12:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d87ed6edd88190afd5063daba58a46 |
completed | April 10, 2026, 4:38 a.m. |
Created at: April 6, 2026, 12:15 p.m.