Triple
T17784771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grabs |
E443988
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Maienfeld |
—
|
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: Maienfeld | Statement: [Grabs, borderedBy, Maienfeld]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maienfeld Context triple: [Grabs, borderedBy, Maienfeld]
-
A.
Maienfeld
chosen
Maienfeld is a historic town in the Swiss canton of Graubünden, best known as the setting of Johanna Spyri’s classic “Heidi” stories.
-
B.
Todenfeld
Todenfeld is a village and district of the town of Rheinbach in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
-
C.
Kummerfeld
Kummerfeld is a small municipality in northern Germany, located in the district of Pinneberg in the state of Schleswig-Holstein.
-
D.
Sennfeld
Sennfeld is a municipality in the Schweinfurt district of Bavaria, Germany, known for its traditional Franconian character and proximity to the city of Schweinfurt.
-
E.
Längenfeld
Längenfeld is a Tyrolean municipality in western Austria known for its alpine scenery and thermal spa resort Aqua Dome in the Ötztal valley.
- 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_69d8b9ef17708190bdf7e2adbf14ddc2 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48791dec0819090d6e88449389fc0 |
completed | April 19, 2026, 7:43 a.m. |
Created at: April 10, 2026, 10:12 a.m.