Triple
T12566829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Westphalia |
E295497
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Hemer |
E868532
|
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: Hemer | Statement: [Province of Westphalia, containsSettlement, Hemer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hemer Context triple: [Province of Westphalia, containsSettlement, Hemer]
-
A.
Hemer
chosen
Hemer is a town in the Märkischer Kreis district of North Rhine-Westphalia, Germany, known for its scenic Sauerland landscape and historical limestone caves.
-
B.
Hemulen
Hemulen is a character from Tove Jansson’s Moomin series, typically portrayed as a tall, earnest, and somewhat pedantic creature obsessed with hobbies like stamp collecting and botany.
-
C.
Hemau
Hemau is a small Bavarian town in southeastern Germany, located in the Upper Palatinate region west of Regensburg.
-
D.
Hanem
Hanem is an Ottoman-era honorific title used for women of high social standing, similar to "lady" or "madam."
-
E.
Hemite
Hemite is a village in Turkey best known as the birthplace of renowned novelist Yaşar Kemal.
- 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_69d6ad9cac2c81908e8a7bed82d1e21d |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d954a325948190994bcfc9d571a3a8 |
completed | April 10, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f655914f908190afbebbec3cb57e73 |
completed | May 2, 2026, 7:50 p.m. |
Created at: April 8, 2026, 11:49 p.m.