Triple
T19439768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leah Schlossberg |
E486315
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Schlossberg |
—
|
NE NERFINISHED |
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: Schlossberg | Statement: [Leah Schlossberg, familyName, Schlossberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schlossberg Context triple: [Leah Schlossberg, familyName, Schlossberg]
-
A.
Schlossberg
Schlossberg is a historic hill in Graz, Austria, known for its fortress ruins, iconic clock tower, and panoramic views over the city.
-
B.
Schlossberg
chosen
Schlossberg is a surname of German origin borne by various notable individuals, including members of the Kennedy family such as Rose Schlossberg.
-
C.
Bocksberg
Bocksberg is a mountain in the Harz region of Germany, known for its hiking trails, winter sports facilities, and scenic views near the village of Hahnenklee.
-
D.
Schlossberg hill
Schlossberg hill is a prominent wooded elevation overlooking the town of Forbach in Germany’s Black Forest region, known for its scenic views and hiking opportunities.
-
E.
Hornberg
Hornberg is a small town in the Black Forest region of Baden-Württemberg, Germany, known for its scenic landscape and traditional cuckoo clock craftsmanship.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8d7ad488190a3373045029b0f3b |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e633637ea48190bfa36b0b0a2762bc |
completed | April 20, 2026, 2:08 p.m. |
Created at: April 10, 2026, 1:38 p.m.