Triple
T7678674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bastia |
E173930
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Terra Nova
Terra Nova is a neighborhood or district within the Corsican city of Bastia, France.
|
E681400
|
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: Terra Nova | Statement: [Bastia, hasPart, Terra Nova]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Terra Nova Context triple: [Bastia, hasPart, Terra Nova]
-
A.
Terra Nova
Terra Nova is a major offshore oil field and production facility located on the Grand Banks off the coast of Newfoundland and Labrador, Canada.
-
B.
Terra Nova
Terra Nova was a British whaling and exploration ship best known for carrying Robert Falcon Scott’s ill-fated Terra Nova Expedition to Antarctica in the early 20th century.
-
C.
Terra Nova
Terra Nova is a science fiction television series set in a dystopian future where humans travel back to prehistoric Earth to save civilization.
-
D.
Ice Land
Ice Land is a frigid, snow- and ice-themed world in Super Mario Bros. 3 known for its slippery terrain and cold-weather enemies.
-
E.
Les Machines de l’Île
Les Machines de l’Île is a large-scale artistic and cultural project in Nantes featuring fantastical mechanical creatures and interactive machines inspired by Jules Verne and Leonardo da Vinci.
- 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: Terra Nova Triple: [Bastia, hasPart, Terra Nova]
Generated description
Terra Nova is a neighborhood or district within the Corsican city of Bastia, France.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Terra Nova Target entity description: Terra Nova is a neighborhood or district within the Corsican city of Bastia, France.
-
A.
Terra Nova
Terra Nova is a major offshore oil field and production facility located on the Grand Banks off the coast of Newfoundland and Labrador, Canada.
-
B.
Terra Nova
Terra Nova is a science fiction television series set in a dystopian future where humans travel back to prehistoric Earth to save civilization.
-
C.
Terra Nova
Terra Nova was a British whaling and exploration ship best known for carrying Robert Falcon Scott’s ill-fated Terra Nova Expedition to Antarctica in the early 20th century.
-
D.
Ice Land
Ice Land is a frigid, snow- and ice-themed world in Super Mario Bros. 3 known for its slippery terrain and cold-weather enemies.
-
E.
Les Machines de l’Île
Les Machines de l’Île is a large-scale artistic and cultural project in Nantes featuring fantastical mechanical creatures and interactive machines inspired by Jules Verne and Leonardo da Vinci.
- 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_69c6995703e0819081de77361b602e78 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c701fd18d88190888144a7d0f228d9 |
completed | March 27, 2026, 10:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8a248750481908f0de08aee78c9ba |
completed | March 29, 2026, 3:53 a.m. |
| NEDg | Description generation | batch_69c8a2fd5a348190a952f6cc3e622474 |
completed | March 29, 2026, 3:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c8a3a570948190ba733c3c858d4bfd |
completed | March 29, 2026, 3:59 a.m. |
Created at: March 27, 2026, 4:01 p.m.