Triple
T715524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hesse |
E14304
|
entity |
| Predicate | containsForest |
P4319
|
FINISHED |
| Object | Spessart |
E97286
|
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: Spessart | Statement: [Hesse, containsForest, Spessart]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Spessart Context triple: [Hesse, containsForest, Spessart]
-
A.
Bohemian Massif
The Bohemian Massif is a large, ancient crystalline highland in Central Europe, spanning parts of the Czech Republic, Germany, Austria, and Poland.
-
B.
Najd
Najd is the central plateau region of Saudi Arabia, historically known as a heartland of Arab tribal culture and the birthplace of the modern Saudi state.
-
C.
Houffalize
Houffalize is a small town in the Belgian Ardennes known for its World War II history, outdoor tourism, and scenic natural surroundings.
-
D.
Breyten
Breyten is the given name of Breyten Breytenbach, the renowned South African poet, painter, and anti-apartheid activist.
-
E.
Taunus
chosen
Taunus is a low mountain range in central Germany known for its forested hills, spa towns, and proximity to the Rhine-Main metropolitan region.
- 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_69a4934a36e081909e7abef98b898a4e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4aa9a1dcc81908bdb7b960765fde5 |
completed | March 1, 2026, 9:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7927e57d48190a9e1f34c39501680 |
completed | March 4, 2026, 2:01 a.m. |
Created at: March 1, 2026, 7:37 p.m.