Triple
T13346555
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christina of Denmark |
E317966
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Christina |
E75185
|
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: Christina | Statement: [Christina of Denmark, givenName, Christina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Christina Context triple: [Christina of Denmark, givenName, Christina]
-
A.
Christina
chosen
Christina is a feminine given name widely used in many cultures, often associated with notable figures in entertainment, arts, and public life.
-
B.
Christina Evangeline
Christina Evangeline is an American model and wellness advocate best known as the former wife of comedian and Saturday Night Live star Kenan Thompson.
-
C.
Christiane
Christiane is the given name of Christiane Nüsslein-Volhard, the Nobel Prize–winning German developmental biologist known for her pioneering work on genetic control of embryonic development.
-
D.
Christianne
Christianne is a feminine given name of Latin origin, commonly used in German- and English-speaking countries.
-
E.
Krista
Krista is a feminine given name, typically considered a variant of Christina and used in various European and English-speaking countries.
- 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_69d806b5a3c08190b42c267fb092f98a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99e89c65c819093f3bea11d6073c5 |
completed | April 11, 2026, 1:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f71f439b3c8190b35fd4d097d65068 |
completed | May 3, 2026, 10:11 a.m. |
Created at: April 9, 2026, 9:31 p.m.