Triple
T2962830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ursula von der Leyen |
E80087
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Ursula
Ursula is a feminine given name of Latin origin, most famously borne by Ursula von der Leyen, the President of the European Commission.
|
E313707
|
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: Ursula | Statement: [Ursula von der Leyen, givenName, Ursula]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ursula Context triple: [Ursula von der Leyen, givenName, Ursula]
-
A.
Ariel
Ariel is the adventurous, red-haired mermaid princess from Disney’s The Little Mermaid, known for her curiosity about the human world and iconic songs like “Part of Your World.”
-
B.
Ariel
Ariel is a spirit of the air and a central supernatural character in William Shakespeare’s play "The Tempest."
-
C.
Ariel
Ariel is a posthumously published poetry collection by Sylvia Plath that is widely regarded as her most powerful and influential work.
-
D.
Ariel
Ariel is one of Uranus's major icy moons, known for its relatively bright surface and complex system of canyons and fault valleys.
-
E.
Erika
Erika is a feminine given name of German origin, borne by numerous notable figures including writer and actress Erika Mann.
- 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: Ursula Triple: [Ursula von der Leyen, givenName, Ursula]
Generated description
Ursula is a feminine given name of Latin origin, most famously borne by Ursula von der Leyen, the President of the European Commission.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ursula Target entity description: Ursula is a feminine given name of Latin origin, most famously borne by Ursula von der Leyen, the President of the European Commission.
-
A.
Ariel
Ariel is the adventurous, red-haired mermaid princess from Disney’s The Little Mermaid, known for her curiosity about the human world and iconic songs like “Part of Your World.”
-
B.
Ariel
Ariel is a spirit of the air and a central supernatural character in William Shakespeare’s play "The Tempest."
-
C.
Ariel
Ariel is a posthumously published poetry collection by Sylvia Plath that is widely regarded as her most powerful and influential work.
-
D.
Ariel
Ariel is one of Uranus's major icy moons, known for its relatively bright surface and complex system of canyons and fault valleys.
-
E.
Erika
Erika is a feminine given name of German origin, borne by numerous notable figures including writer and actress Erika Mann.
- 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_69ad8b1341848190bd19dbf46892887d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9957602c819089b673966fd619e0 |
completed | March 8, 2026, 3:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b0fc959b3c8190a0d95a3e616246f9 |
completed | March 11, 2026, 5:24 a.m. |
| NEDg | Description generation | batch_69b0fd6caf508190b45a396d1402ca65 |
completed | March 11, 2026, 5:28 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b0fdcffa8081908e1c1392306ff7af |
completed | March 11, 2026, 5:29 a.m. |
Created at: March 8, 2026, 2:57 p.m.