Triple
T9345606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince of Lüneburg |
E224881
|
entity |
| Predicate | hasSeat |
P3522
|
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: [Prince of Lüneburg, hasSeat, Celle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Celle Context triple: [Prince of Lüneburg, hasSeat, 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.
Cellese
Cellese is a regional dialect of the Franco-Provençal language traditionally spoken in a specific area of the Franco-Provençal linguistic region.
-
C.
Schierke
Schierke is a small village in the Harz Mountains of Germany, known as a gateway to the Brocken peak and for its historic narrow-gauge railway connections and winter sports tourism.
-
D.
Celles
Celles is a small French village in the Hérault department of southern France, known for its picturesque location on the shores of the artificial Lac du Salagou.
-
E.
Delle
Delle is a small commune in northeastern France near the Swiss border, known as a local administrative and economic center in the Territoire de Belfort department.
- 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_69ca842993248190a79ab06968994b86 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd4f0e2ccc8190a68f1c96c0886660 |
completed | April 1, 2026, 4:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0e41ccdcc8190b2939716984b2c7b |
completed | April 4, 2026, 10:12 a.m. |
Created at: March 30, 2026, 7:41 p.m.