Triple
T12535575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christiana Barkley |
E299680
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Christiana |
E618173
|
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: Christiana | Statement: [Christiana Barkley, givenName, Christiana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Christiana Context triple: [Christiana Barkley, givenName, Christiana]
-
A.
Christiana
chosen
Christiana is a personal name used as a given name, notably borne by individuals such as Christiana Wyly.
-
B.
Christiana
Christiana is a prominent inland town in central Jamaica known as a commercial and agricultural hub within the parish of Manchester.
-
C.
Bernardine
Bernardine is a 1957 musical comedy film starring Pat Boone in one of his early leading screen roles.
-
D.
Bridgitt
Bridgitt is a given name that functions as an alternative spelling of the name Bridgette.
-
E.
Clementina
Clementina is a feminine given name, often considered a variant of Clementine, used in various European and Latin American cultures.
- 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_69d6ada707008190aaec1238117c9379 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9546d3b2081908d3e0659f8f13678 |
completed | April 10, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f65577e3388190b6c1c2e8dee7f6ac |
completed | May 2, 2026, 7:50 p.m. |
Created at: April 8, 2026, 9:57 p.m.