Triple
T17292004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Count of Nassau-Weilburg |
E419806
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Weilburg |
E145657
|
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: Weilburg | Statement: [Count of Nassau-Weilburg, locatedIn, Weilburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Weilburg Context triple: [Count of Nassau-Weilburg, locatedIn, Weilburg]
-
A.
Weilburg
chosen
Weilburg is a historic town in the German state of Hesse, known for its Renaissance castle and as the ancestral seat of the House of Nassau-Weilburg.
-
B.
Limburg-Weilburg
Limburg-Weilburg is a rural district in the German state of Hesse, known for its historic town of Limburg an der Lahn and its location along the Lahn River.
-
C.
Morbach
Morbach is a small town in the Hunsrück region of Rhineland-Palatinate in western Germany, known for its scenic forests and rural landscapes.
-
D.
Willebadessen
Willebadessen is a small town in western Germany, located in the state of North Rhine-Westphalia.
-
E.
Bruchsal
Bruchsal is a town in the state of Baden-Württemberg in southwestern Germany, known for its baroque palace and asparagus cultivation.
- 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_69d886db32608190a61e18862c5a8af6 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e4378438508190924f732ad748b4d0 |
completed | April 19, 2026, 2:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a017959ffb0819099d70ed1541158ee |
completed | May 11, 2026, 6:38 a.m. |
Created at: April 10, 2026, 5:40 a.m.