Triple
T14677680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marianne Huber |
E344690
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object | Marianne |
E729059
|
NE FINISHED |
How this triple was built (2 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: Marianne | Statement: [Marianne Huber, hasGivenName, Marianne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marianne Context triple: [Marianne Huber, hasGivenName, Marianne]
-
A.
Marianne
chosen
Marianne is a feminine given name of French origin that has been widely used in various cultures and is often associated with grace and classic elegance.
-
B.
Marianne
Marianne was a 19th-century Dutch princess of the House of Orange-Nassau, known for her independent spirit, unconventional personal life, and extensive patronage of the arts and architecture.
-
C.
Marianne
Marianne is the national personification of the French Republic, symbolizing liberty, reason, and the values of the nation.
-
D.
Marianne
Marianne is the central female figure addressed in Leonard Cohen's song "So Long, Marianne," widely recognized as a muse-like character in his work.
-
E.
Marianne
Marianne is the central protagonist of the horror film "In Fabric," whose experiences with a cursed red dress drive the movie's surreal and unsettling narrative.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d822e34b348190ada4d1cdb6c7c226 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb567c2b88190a9639e61b6fba7df |
completed | April 14, 2026, 9:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fde17e5a1c8190b1bf5565eab9d519 |
completed | May 8, 2026, 1:13 p.m. |
Created at: April 10, 2026, 1:27 a.m.