Triple
T12528798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unkel |
E299505
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object | Heister |
E799383
|
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: Heister | Statement: [Unkel, hasSubdivision, Heister]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Heister Context triple: [Unkel, hasSubdivision, Heister]
-
A.
de Heister
De Heister is a German noble family name historically associated with military officers and aristocrats, including the Hessian general Leopold Philip de Heister.
-
B.
Heris
Heris is a city in northwestern Iran known for its traditional handwoven carpets and rugs.
-
C.
Haiger
chosen
Haiger is a small town in the German state of Hesse, known for its location in the Lahn-Dill district near the borders with North Rhine-Westphalia and Rhineland-Palatinate.
-
D.
Rodemack
Rodemack is a historic fortified village in northeastern France, renowned for its well-preserved medieval ramparts and picturesque old town.
-
E.
Dirck
Dirck is a Dutch masculine given name historically borne by several notable figures, including artists of the Dutch Golden Age.
- 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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9545e90948190980bd4d64964a0f2 |
completed | April 10, 2026, 7:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f64bc674e881908673e1f9103cc8be |
completed | May 2, 2026, 7:08 p.m. |
Created at: April 8, 2026, 9:57 p.m.