Triple
T16158265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Graben |
E392108
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object | Ankerhaus |
E1117263
|
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: Ankerhaus | Statement: [Graben, hasLandmark, Ankerhaus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ankerhaus Context triple: [Graben, hasLandmark, Ankerhaus]
-
A.
Ankerhaus
chosen
Ankerhaus is a notable historic building in Vienna, Austria, recognized for its distinctive architecture and prominent location on the Graben.
-
B.
Lucknerhaus
Lucknerhaus is a mountain hut and popular starting point for alpine tours in the Austrian Alps, particularly in the Großglockner area.
-
C.
Almenhof
Almenhof is a residential district of Mannheim in the German state of Baden-Württemberg.
-
D.
Woermannhaus
Woermannhaus is a historic German colonial-era building in Swakopmund, Namibia, known for its distinctive architecture and prominent tower.
-
E.
Fischerhäuser
Fischerhäuser is a small locality that forms part of the municipality of Inning am Ammersee in Bavaria, Germany.
- 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_69d87f1c65e48190aa2b4c472e9bafc4 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21e5c9cd0819090e34ee163ffb118 |
completed | April 17, 2026, 11:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff7b05a588190a44d1c922195a87b |
completed | May 10, 2026, 3:12 a.m. |
Created at: April 10, 2026, 5:01 a.m.