Triple
T8647074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eugenius Warming |
E205002
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object |
Mandø
Mandø is a small Danish island in the Wadden Sea, known for its tidal causeway access, rich birdlife, and traditional marshland landscapes.
|
E749596
|
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: Mandø | Statement: [Eugenius Warming, placeOfBirth, Mandø]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mandø Context triple: [Eugenius Warming, placeOfBirth, Mandø]
-
A.
Rømø
Rømø is a Danish island in the Wadden Sea known for its expansive sandy beaches, coastal dunes, and popular holiday resorts.
-
B.
Langeland
Langeland is a Danish island in the South Funen Archipelago, known for its rural landscapes, coastal scenery, and historical villages.
-
C.
Møn
Møn is a Danish island in the Baltic Sea known for its dramatic white chalk cliffs, scenic landscapes, and rich prehistoric and cultural heritage.
-
D.
Hvidøen
Hvidøen is the former name of Kvitøya, a remote, ice-covered island in the Svalbard archipelago of the Arctic Ocean.
-
E.
Læsø
Læsø is a Danish island in the Kattegat known for its salt production, distinctive seaweed-roofed houses, and tranquil coastal landscapes.
- 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: Mandø Triple: [Eugenius Warming, placeOfBirth, Mandø]
Generated description
Mandø is a small Danish island in the Wadden Sea, known for its tidal causeway access, rich birdlife, and traditional marshland landscapes.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mandø Target entity description: Mandø is a small Danish island in the Wadden Sea, known for its tidal causeway access, rich birdlife, and traditional marshland landscapes.
-
A.
Rømø
Rømø is a Danish island in the Wadden Sea known for its expansive sandy beaches, coastal dunes, and popular holiday resorts.
-
B.
Langeland
Langeland is a Danish island in the South Funen Archipelago, known for its rural landscapes, coastal scenery, and historical villages.
-
C.
Møn
Møn is a Danish island in the Baltic Sea known for its dramatic white chalk cliffs, scenic landscapes, and rich prehistoric and cultural heritage.
-
D.
Hvidøen
Hvidøen is the former name of Kvitøya, a remote, ice-covered island in the Svalbard archipelago of the Arctic Ocean.
-
E.
Læsø
Læsø is a Danish island in the Kattegat known for its salt production, distinctive seaweed-roofed houses, and tranquil coastal landscapes.
- 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_69ca834e56848190abb0eeaec9dedd32 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc48112b4881908901214f41b6bf71 |
completed | March 31, 2026, 10:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ceccb8b91881908630f3e4c4461af4 |
completed | April 2, 2026, 8:08 p.m. |
| NEDg | Description generation | batch_69cece1681288190a6c99407bc2f0bdd |
completed | April 2, 2026, 8:14 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cecec118ac81909fbcafe841354c32 |
completed | April 2, 2026, 8:17 p.m. |
Created at: March 30, 2026, 6:29 p.m.