Triple
T3689020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harz Narrow Gauge Railways |
E78298
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
HSB
HSB is a historic narrow-gauge railway network in Germany’s Harz mountains, popular for its steam-powered tourist trains and scenic routes.
|
E379330
|
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: HSB | Statement: [Harz Narrow Gauge Railways, abbreviation, HSB]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HSB Context triple: [Harz Narrow Gauge Railways, abbreviation, HSB]
-
A.
HSB
HSB is a specialty insurance and engineering services company best known for its expertise in equipment breakdown coverage and risk management solutions.
-
B.
HUES
HUES is the commonly used acronym for the Graduate School of Human-Environment Studies, an academic institution focused on interdisciplinary research and education on the interactions between people and their environments.
-
C.
BGR
BGR is the three-letter ISO 3166-1 alpha-3 country code assigned to Bulgaria.
-
D.
BGR
BGR is the three-letter IATA airport code for Bangor International Airport in Bangor, Maine, United States.
-
E.
Hue
Hue is a historic city in central Vietnam that served as the former imperial capital and was a major battleground during the Vietnam War.
- 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: HSB Triple: [Harz Narrow Gauge Railways, abbreviation, HSB]
Generated description
HSB is a historic narrow-gauge railway network in Germany’s Harz mountains, popular for its steam-powered tourist trains and scenic routes.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: HSB Target entity description: HSB is a historic narrow-gauge railway network in Germany’s Harz mountains, popular for its steam-powered tourist trains and scenic routes.
-
A.
HSB
HSB is a specialty insurance and engineering services company best known for its expertise in equipment breakdown coverage and risk management solutions.
-
B.
HUES
HUES is the commonly used acronym for the Graduate School of Human-Environment Studies, an academic institution focused on interdisciplinary research and education on the interactions between people and their environments.
-
C.
BGR
BGR is the three-letter ISO 3166-1 alpha-3 country code assigned to Bulgaria.
-
D.
BGR
BGR is the three-letter IATA airport code for Bangor International Airport in Bangor, Maine, United States.
-
E.
Hue
Hue is a historic city in central Vietnam that served as the former imperial capital and was a major battleground during the Vietnam War.
- 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_69ad85e285a081908f8cbfa9e2ed9b75 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc4cb47208190b1321af859d02c51 |
completed | March 8, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4c3c5b6488190afb8cc599d633a96 |
completed | March 14, 2026, 2:11 a.m. |
| NEDg | Description generation | batch_69b4c463b53c8190b3333fda95862545 |
completed | March 14, 2026, 2:13 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4c4ee4db88190810a1d49d757b2b6 |
completed | March 14, 2026, 2:16 a.m. |
Created at: March 8, 2026, 3:26 p.m.