Triple
T3516001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dutch railway network |
E74308
|
entity |
| Predicate | hasHighSpeedLine |
P48478
|
FINISHED |
| Object |
Hanzelijn
Hanzelijn is a Dutch railway line connecting Lelystad and Zwolle, designed to shorten travel times between the Randstad and the northern Netherlands and partially built for higher-speed services.
|
E364990
|
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: Hanzelijn | Statement: [Dutch railway network, hasHighSpeedLine, Hanzelijn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hanzelijn Context triple: [Dutch railway network, hasHighSpeedLine, Hanzelijn]
-
A.
Heenweg
Heenweg is a small village in the Dutch municipality of Westland in the province of South Holland, Netherlands.
-
B.
Achterhooks
Achterhooks is a regional Low Saxon dialect spoken in the Achterhoek area of the eastern Netherlands.
-
C.
Haselünne
Haselünne is a small historic town in Lower Saxony, Germany, known for its traditional grain distilleries and picturesque setting along the Hase River.
-
D.
Bonte
Bonte is a German surname most notably borne by Friedrich Bonte, a Kriegsmarine officer during World War II.
-
E.
Maartenszen
Maartenszen is a Dutch patronymic surname indicating "son of Maarten," historically used in the Netherlands.
- 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: Hanzelijn Triple: [Dutch railway network, hasHighSpeedLine, Hanzelijn]
Generated description
Hanzelijn is a Dutch railway line connecting Lelystad and Zwolle, designed to shorten travel times between the Randstad and the northern Netherlands and partially built for higher-speed services.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hanzelijn Target entity description: Hanzelijn is a Dutch railway line connecting Lelystad and Zwolle, designed to shorten travel times between the Randstad and the northern Netherlands and partially built for higher-speed services.
-
A.
Heenweg
Heenweg is a small village in the Dutch municipality of Westland in the province of South Holland, Netherlands.
-
B.
Achterhooks
Achterhooks is a regional Low Saxon dialect spoken in the Achterhoek area of the eastern Netherlands.
-
C.
Haselünne
Haselünne is a small historic town in Lower Saxony, Germany, known for its traditional grain distilleries and picturesque setting along the Hase River.
-
D.
Bonte
Bonte is a German surname most notably borne by Friedrich Bonte, a Kriegsmarine officer during World War II.
-
E.
Maartenszen
Maartenszen is a Dutch patronymic surname indicating "son of Maarten," historically used in the Netherlands.
- 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_69ad85cfb5c881909c9a2edd9d6043cc |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc30362c81908ca7497a6a935cc6 |
completed | March 8, 2026, 6:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b37e7da9c08190ab417b45339513bd |
completed | March 13, 2026, 3:03 a.m. |
| NEDg | Description generation | batch_69b37f61b4a88190b36ada98f063edcf |
completed | March 13, 2026, 3:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b37fbec2ec81909228716c70ffa2bd |
completed | March 13, 2026, 3:08 a.m. |
Created at: March 8, 2026, 3:19 p.m.