Triple
T12682360
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ins |
E302977
|
entity |
| Predicate | hasNeighboringMunicipality |
P224
|
FINISHED |
| Object | Erlach |
E986761
|
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: Erlach | Statement: [Ins, hasNeighboringMunicipality, Erlach]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Erlach Context triple: [Ins, hasNeighboringMunicipality, Erlach]
-
A.
Erlach
chosen
Erlach is a small historic town in the Swiss canton of Bern, situated on the shores of Lake Biel and known for its winegrowing and scenic lakeside setting.
-
B.
Erasbach
Erasbach is a small locality in Bavaria, Germany, best known as the birthplace of the composer Christoph Willibald Gluck.
-
C.
Hohberg
Hohberg is a municipality in the Ortenau district of Baden-Württemberg in southwestern Germany.
-
D.
Elbling
Elbling is an ancient white wine grape variety primarily cultivated in Germany and Luxembourg, known for producing light, crisp, and high-acidity wines.
-
E.
Haller
Haller is a surname most notably associated with Ernest Haller, an American cinematographer renowned for his work in classic Hollywood films.
- 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_69d7bdee64a08190801c6d470aefd723 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961d68358819095bdaab8adf1dcf0 |
completed | April 10, 2026, 8:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f671a733a48190b55d296573c86eaf |
completed | May 2, 2026, 9:50 p.m. |
Created at: April 9, 2026, 5:21 p.m.