Triple
T730476
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warrington |
E14818
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object |
Hilden
Hilden is a town in western Germany’s North Rhine-Westphalia region, known for its proximity to Düsseldorf and its mix of residential, commercial, and light industrial areas.
|
E103803
|
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: Hilden | Statement: [Warrington, hasTwinTown, Hilden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hilden Context triple: [Warrington, hasTwinTown, Hilden]
-
A.
Lünen
Lünen is a town in North Rhine-Westphalia, Germany, known as an industrial and commuter city in the Ruhr area.
-
B.
Delmenhorst
Delmenhorst is a mid-sized industrial and commuter city in northwestern Germany, located near Bremen in the federal state of Lower Saxony.
-
C.
Starnberg
Starnberg is a lakeside town in Bavaria, Germany, known for its affluent residential character and scenic location on Lake Starnberg southwest of Munich.
-
D.
Badhoevedorp
Badhoevedorp is a village in North Holland, Netherlands, located just southwest of Amsterdam and known for its proximity to Schiphol Airport.
-
E.
Haninge Municipality
Haninge Municipality is a local government area in east-central Sweden that forms part of the greater Stockholm metropolitan region.
- 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: Hilden Triple: [Warrington, hasTwinTown, Hilden]
Generated description
Hilden is a town in western Germany’s North Rhine-Westphalia region, known for its proximity to Düsseldorf and its mix of residential, commercial, and light industrial areas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hilden Target entity description: Hilden is a town in western Germany’s North Rhine-Westphalia region, known for its proximity to Düsseldorf and its mix of residential, commercial, and light industrial areas.
-
A.
Lünen
Lünen is a town in North Rhine-Westphalia, Germany, known as an industrial and commuter city in the Ruhr area.
-
B.
Delmenhorst
Delmenhorst is a mid-sized industrial and commuter city in northwestern Germany, located near Bremen in the federal state of Lower Saxony.
-
C.
Starnberg
Starnberg is a lakeside town in Bavaria, Germany, known for its affluent residential character and scenic location on Lake Starnberg southwest of Munich.
-
D.
Badhoevedorp
Badhoevedorp is a village in North Holland, Netherlands, located just southwest of Amsterdam and known for its proximity to Schiphol Airport.
-
E.
Haninge Municipality
Haninge Municipality is a local government area in east-central Sweden that forms part of the greater Stockholm metropolitan region.
- 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_69a4934d9930819099eed80096b0597d |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a5c290e481908497430a05dbfb90 |
completed | March 1, 2026, 8:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7b83709248190bee17ec028b12bae |
completed | March 4, 2026, 4:42 a.m. |
| NEDg | Description generation | batch_69a7b93aed5c8190b5a588ed4a5eb94d |
completed | March 4, 2026, 4:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a7b9bb13f08190ad75518ba81b210d |
completed | March 4, 2026, 4:48 a.m. |
Created at: March 1, 2026, 7:37 p.m.