Triple
T10835190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | River Pleiße |
E255735
|
entity |
| Predicate | passesNear |
P416
|
FINISHED |
| Object | Altenburg |
E296758
|
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: Altenburg | Statement: [River Pleiße, passesNear, Altenburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Altenburg Context triple: [River Pleiße, passesNear, Altenburg]
-
A.
Altenburg
chosen
Altenburg is a historic town in eastern Thuringia, Germany, known for its playing-card tradition and as the birthplace of the card game Skat.
-
B.
Kronach
Kronach is a historic town in northern Bavaria, Germany, known for its well-preserved medieval old town and the imposing Rosenberg Fortress.
-
C.
Altenstadt
Altenstadt is a small Bavarian municipality in southern Germany, situated within the rural district of Weilheim-Schongau.
-
D.
Wettin
Wettin is a small town in Saxony-Anhalt, Germany, historically significant as the ancestral seat of the influential House of Wettin.
-
E.
Rudolstadt
Rudolstadt is a historic town in the German state of Thuringia, known for its picturesque old town, Heidecksburg Castle, and cultural festivals.
- 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_69d6aa81a5d08190aa86689061d1ddd2 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d746fdefd4819099772efbd4f302cb |
completed | April 9, 2026, 6:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e712b2ff1081908ccf311e1133ab72 |
completed | April 21, 2026, 6:01 a.m. |
Created at: April 8, 2026, 9:19 p.m.