Triple
T22319575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thierstein district |
E551745
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object |
Fehren
Fehren is a small Swiss municipality located in the canton of Solothurn.
|
E1531758
|
NE FINISHED |
How this triple was built (4 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: Fehren | Statement: [Thierstein district, containsMunicipality, Fehren]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fehren Context triple: [Thierstein district, containsMunicipality, Fehren]
-
A.
Ferenberg
Ferenberg is a small locality within the municipality of Bolligen in the canton of Bern, Switzerland.
-
B.
Felden
Felden is a residential area on the outskirts of Hemel Hempstead in Hertfordshire, England, known for its leafy surroundings and proximity to the Chilterns.
-
C.
Flerzheim
Flerzheim is a village and district of the town of Rheinbach in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
-
D.
Faehn
Faehn is a surname most notably associated with Rhonda Faehn, an American former elite gymnast and influential gymnastics coach and administrator.
-
E.
Feresten
Feresten is the surname of Spike Feresten, an American television writer, comedian, and talk show host known for his work on shows like Seinfeld and Late Show with David Letterman.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Fehren Triple: [Thierstein district, containsMunicipality, Fehren]
Generated description
Fehren is a small Swiss municipality located in the canton of Solothurn.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Fehren Target entity description: Fehren is a small Swiss municipality located in the canton of Solothurn.
-
A.
Ferenberg
Ferenberg is a small locality within the municipality of Bolligen in the canton of Bern, Switzerland.
-
B.
Felden
Felden is a residential area on the outskirts of Hemel Hempstead in Hertfordshire, England, known for its leafy surroundings and proximity to the Chilterns.
-
C.
Flerzheim
Flerzheim is a village and district of the town of Rheinbach in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
-
D.
Faehn
Faehn is a surname most notably associated with Rhonda Faehn, an American former elite gymnast and influential gymnastics coach and administrator.
-
E.
Feresten
Feresten is the surname of Spike Feresten, an American television writer, comedian, and talk show host known for his work on shows like Seinfeld and Late Show with David Letterman.
- F. None of above. chosen
Provenance (5 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_69e11e4776588190abb21e5cea79973f |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15762fac08190a6a514baffbbbca1 |
completed | April 29, 2026, 12:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0ad5174c20819090b3f7ffd85a8376 |
completed | May 18, 2026, 9 a.m. |
| NEDg | Description generation | batch_6a0ad991a1e48190ad240a20694223fc |
completed | May 18, 2026, 9:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0ada2a61b881908a636b2d1d6e4509 |
completed | May 18, 2026, 9:21 a.m. |
Created at: April 16, 2026, 8:42 p.m.