Triple
T10088209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boxmoor |
E215273
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object |
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.
|
E841114
|
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: Felden | Statement: [Boxmoor, adjacentTo, Felden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Felden Context triple: [Boxmoor, adjacentTo, Felden]
-
A.
Maienfeld
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.
Friedberg
Friedberg is a historic German town in the state of Hesse, known for its medieval fortifications and strategic importance during the Seven Years' War.
-
D.
Längenfeld
Längenfeld is a Tyrolean municipality in western Austria known for its alpine scenery and thermal spa resort Aqua Dome in the Ötztal valley.
-
E.
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.
- 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: Felden Triple: [Boxmoor, adjacentTo, Felden]
Generated description
Felden is a residential area on the outskirts of Hemel Hempstead in Hertfordshire, England, known for its leafy surroundings and proximity to the Chilterns.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Felden Target entity description: Felden is a residential area on the outskirts of Hemel Hempstead in Hertfordshire, England, known for its leafy surroundings and proximity to the Chilterns.
-
A.
Maienfeld
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.
Friedberg
Friedberg is a historic German town in the state of Hesse, known for its medieval fortifications and strategic importance during the Seven Years' War.
-
D.
Längenfeld
Längenfeld is a Tyrolean municipality in western Austria known for its alpine scenery and thermal spa resort Aqua Dome in the Ötztal valley.
-
E.
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.
- 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_69ca83a1eed081908b2e9580f2ebeea7 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd04875748190a81d1e9ad68dda96 |
completed | April 2, 2026, 2:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2b693afac819090635d2eb147bdcb |
completed | April 5, 2026, 7:22 p.m. |
| NEDg | Description generation | batch_69d2b7aecdb081909f651c1bc1bcfd75 |
completed | April 5, 2026, 7:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d2b86bf8948190a79046efadc4adea |
completed | April 5, 2026, 7:30 p.m. |
Created at: March 30, 2026, 9:01 p.m.