Triple
T22124330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emanuel Vigeland |
E546753
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Emanuel |
—
|
NE NERFINISHED |
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: Emanuel | Statement: [Emanuel Vigeland, givenName, Emanuel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Emanuel Context triple: [Emanuel Vigeland, givenName, Emanuel]
-
A.
Emanuel
Emanuel is a surname most prominently associated with Rahm Emanuel, the American politician and former mayor of Chicago.
-
B.
Emmanuel
Emmanuel is a Belgian prince, a member of the royal family of Belgium and the son of King Philippe and Queen Mathilde.
-
C.
Emmanuel
chosen
Emmanuel is a masculine given name of Hebrew origin meaning "God is with us," used in various languages and cultures.
-
D.
Emmanuel Kadosh
Emmanuel Kadosh is a cinematographer known for his work on the adventure-comedy film "The Lost City."
-
E.
Emanuel Christ
Emanuel Christ is a Swiss architect best known as a co-founder and partner of the Basel-based architecture firm Christ & Gantenbein.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e39bf348190b541bfa16a7b71e0 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1298016e081909d00015ca516d9fd |
completed | April 28, 2026, 9:41 p.m. |
Created at: April 16, 2026, 8:31 p.m.