Triple
T2429751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mersey Ferry |
E52813
|
entity |
| Predicate | hasVessel |
P26083
|
FINISHED |
| Object |
Snowdrop
Snowdrop is a Mersey Ferry passenger vessel that operates on the River Mersey, carrying commuters and tourists between Liverpool and the Wirral.
|
E264861
|
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: Snowdrop | Statement: [Mersey Ferry, hasVessel, Snowdrop]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Snowdrop Context triple: [Mersey Ferry, hasVessel, Snowdrop]
-
A.
Snowdrops
Snowdrops is an informal nickname for members of the Royal Air Force Police in the United Kingdom.
-
B.
Edelweiss
"Edelweiss" is a gentle, nostalgic song from the musical *The Sound of Music*, widely recognized as one of Richard Rodgers and Oscar Hammerstein II’s most beloved compositions.
-
C.
The Flower
The Flower is the nickname of Guy Lafleur, the legendary Montreal Canadiens right winger renowned for his speed, scoring prowess, and flowing blond hair.
-
D.
Irises
Irises is a famous 1889 oil painting by Vincent van Gogh depicting a vibrant cluster of blooming irises, celebrated for its expressive color and dynamic composition.
-
E.
Iris
Iris is a 2001 British biographical drama film about the life and relationships of novelist and philosopher Iris Murdoch.
- 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: Snowdrop Triple: [Mersey Ferry, hasVessel, Snowdrop]
Generated description
Snowdrop is a Mersey Ferry passenger vessel that operates on the River Mersey, carrying commuters and tourists between Liverpool and the Wirral.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Snowdrop Target entity description: Snowdrop is a Mersey Ferry passenger vessel that operates on the River Mersey, carrying commuters and tourists between Liverpool and the Wirral.
-
A.
Snowdrops
Snowdrops is an informal nickname for members of the Royal Air Force Police in the United Kingdom.
-
B.
Edelweiss
"Edelweiss" is a gentle, nostalgic song from the musical *The Sound of Music*, widely recognized as one of Richard Rodgers and Oscar Hammerstein II’s most beloved compositions.
-
C.
The Flower
The Flower is the nickname of Guy Lafleur, the legendary Montreal Canadiens right winger renowned for his speed, scoring prowess, and flowing blond hair.
-
D.
Irises
Irises is a famous 1889 oil painting by Vincent van Gogh depicting a vibrant cluster of blooming irises, celebrated for its expressive color and dynamic composition.
-
E.
Iris
Iris is a 2001 British biographical drama film about the life and relationships of novelist and philosopher Iris Murdoch.
- 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_69ab4959bcc0819083246f9fb10439e3 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abc99fcd048190a85b95a9a8ae6d4d |
completed | March 7, 2026, 6:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aebf6634a48190af82eab6b9750323 |
completed | March 9, 2026, 12:39 p.m. |
| NEDg | Description generation | batch_69aec2a3f4708190a6c51f28833174e3 |
completed | March 9, 2026, 12:52 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69aec3626a7081908f1ccef98e9b96be |
completed | March 9, 2026, 12:56 p.m. |
Created at: March 6, 2026, 9:43 p.m.