Triple
T16109971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oststadt (Hanover) |
E390846
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object |
List (Hanover)
List is a central district of Hanover, Germany, known for its residential character, green spaces, and vibrant urban life.
|
E1194886
|
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: List (Hanover) | Statement: [Oststadt (Hanover), borderedBy, List (Hanover)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: List (Hanover) Context triple: [Oststadt (Hanover), borderedBy, List (Hanover)]
-
A.
Halnaker
Halnaker is a small village in West Sussex, England, known for its historic windmill and picturesque countryside near the South Downs.
-
B.
Haverstock
Haverstock is an electoral ward in the London Borough of Camden, England.
-
C.
Harlington
Harlington is a village in the London Borough of Hillingdon, England, known for its proximity to Heathrow Airport and its mix of residential areas and local amenities.
-
D.
Rowley
Rowley is a small historic town in northeastern Massachusetts known for its colonial heritage and rural New England character.
-
E.
Rowley
Rowley is a surname of English origin borne by various notable individuals across fields such as politics, science, and the arts.
- 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: List (Hanover) Triple: [Oststadt (Hanover), borderedBy, List (Hanover)]
Generated description
List is a central district of Hanover, Germany, known for its residential character, green spaces, and vibrant urban life.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: List (Hanover) Target entity description: List is a central district of Hanover, Germany, known for its residential character, green spaces, and vibrant urban life.
-
A.
Halnaker
Halnaker is a small village in West Sussex, England, known for its historic windmill and picturesque countryside near the South Downs.
-
B.
Haverstock
Haverstock is an electoral ward in the London Borough of Camden, England.
-
C.
Harlington
Harlington is a village in the London Borough of Hillingdon, England, known for its proximity to Heathrow Airport and its mix of residential areas and local amenities.
-
D.
Rowley
Rowley is a small historic town in northeastern Massachusetts known for its colonial heritage and rural New England character.
-
E.
Rowley
Rowley is a surname of English origin borne by various notable individuals across fields such as politics, science, and the arts.
- 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_69d87f1a8dd881909f1de6ef78849874 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2016665c0819081aa7a44b1d08183 |
completed | April 17, 2026, 9:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffeba674788190a589104cf90f28d5 |
completed | May 10, 2026, 2:21 a.m. |
| NEDg | Description generation | batch_69ffed6638788190a94b87c849dcfbc7 |
completed | May 10, 2026, 2:28 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffee1cb2f88190b489160245a9828a |
completed | May 10, 2026, 2:31 a.m. |
Created at: April 10, 2026, 5 a.m.