Triple
T1585725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bobbi Kristina Brown |
E34060
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Kristina |
E58213
|
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: Kristina | Statement: [Bobbi Kristina Brown, givenName, Kristina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kristina Context triple: [Bobbi Kristina Brown, givenName, Kristina]
-
A.
Katarina Frostenson
Katarina Frostenson is a Swedish poet, writer, and former member of the Swedish Academy known for her influential and experimental contributions to contemporary Swedish literature.
-
B.
Katrin
chosen
Katrin is a feminine given name, commonly used in various European countries, that is a variant of the name Catherine.
-
C.
Margareta
Margareta is a feminine given name used in various European languages, closely related to and derived from the name Margaret.
-
D.
Dagmar
Dagmar is a feminine given name of Germanic origin, historically associated with European nobility and still used in various countries today.
-
E.
Christina
Christina is a feminine given name widely used in many cultures, often associated with notable figures in entertainment, arts, and public life.
- 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_69a885fceb2c8190b47e0f7c0aefbff0 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a908f3b5f48190bd5eff3ce81c5ffb |
completed | March 5, 2026, 4:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad4037bbdc81909bcf9c5c7a7f5de5 |
completed | March 8, 2026, 9:24 a.m. |
Created at: March 4, 2026, 7:27 p.m.