Triple
T11314843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cristel Carrisi |
E267938
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Cristel |
E853045
|
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: Cristel | Statement: [Cristel Carrisi, givenName, Cristel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cristel Context triple: [Cristel Carrisi, givenName, Cristel]
-
A.
Crist
Crist is a surname most prominently associated with American politician Charlie Crist, a former governor of Florida.
-
B.
Kristel
chosen
Kristel is a given name commonly used for women in various countries, often considered a variant of Crystal/Krystal.
-
C.
Cristolienne
Cristolienne is the French term for a female inhabitant or native of the city of Créteil, located in the southeastern suburbs of Paris.
-
D.
Cristeta
Cristeta is a Filipina-American chef best known as the longtime White House Executive Chef.
-
E.
Christianne
Christianne is a feminine given name of Latin origin, commonly used in German- 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_69d6aaca5c24819083db46a30d86cb34 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9c2c7b081909af8acebc8aa93aa |
completed | April 9, 2026, 6:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e50a9e66588190b71e0f60133a8995 |
completed | April 19, 2026, 5:02 p.m. |
Created at: April 8, 2026, 9:32 p.m.