Triple
T607893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bergen-Belsen |
E12033
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Celle |
E30373
|
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: Celle | Statement: [Bergen-Belsen, locatedNear, Celle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Celle Context triple: [Bergen-Belsen, locatedNear, Celle]
-
A.
Celle
chosen
Celle is a historic town in northern Germany renowned for its well-preserved half-timbered old town and ducal palace.
-
B.
Agria
Agria is a coastal town in the Magnesia regional unit of Thessaly, Greece, near the city of Volos.
-
C.
Rednitz
The Rednitz is a river in Bavaria, Germany, that flows through cities such as Fürth and joins with the Pegnitz to form the Regnitz.
-
D.
Sauvy
Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
-
E.
Mouton
Mouton is an academic publishing house known for its influential works in linguistics and related fields.
- 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_69a493309df48190a327f748e88049a6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49df34abc8190a578c8c2ab3d28e4 |
completed | March 1, 2026, 8:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a52eab1dc88190892cf500465db72a |
completed | March 2, 2026, 6:31 a.m. |
Created at: March 1, 2026, 7:35 p.m.