Triple
T19659093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schrankogel |
E472029
|
entity |
| Predicate | hasSummitViewOf |
P9193
|
FINISHED |
| Object | Habicht |
—
|
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: Habicht | Statement: [Schrankogel, hasSummitViewOf, Habicht]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Habicht Context triple: [Schrankogel, hasSummitViewOf, Habicht]
-
A.
Habicht
chosen
Habicht is a prominent mountain peak in the Stubai Alps of Tyrol, Austria, known for its striking pyramid shape and popularity among experienced climbers.
-
B.
Hölldobler
Hölldobler is a German surname most notably associated with Bert Hölldobler, a prominent behavioral ecologist and myrmecologist known for his research on ants.
-
C.
Burkard
Burkard is a surname of German origin borne by various individuals and families around the world.
-
D.
Bischoffen
Bischoffen is a small municipality in the central German state of Hesse, situated in a rural area characterized by forests, hills, and nearby reservoirs.
-
E.
Schwarzhuber
Schwarzhuber is a German surname most notably associated with Johann Schwarzhuber, an SS officer and concentration camp official during World War II.
- 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_69d8e51395348190ac1416d46dfc6db0 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e641485ce481908b3860fa5e3a9f6e |
completed | April 20, 2026, 3:07 p.m. |
Created at: April 10, 2026, 1:45 p.m.