Triple
T15618030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Krista |
E375468
|
entity |
| Predicate | spellingVariantOf |
P457
|
FINISHED |
| Object | Christa |
E207465
|
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: Christa | Statement: [Krista, spellingVariantOf, Christa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Christa Context triple: [Krista, spellingVariantOf, Christa]
-
A.
Christa
chosen
Christa was the first name of Christa McAuliffe, the American teacher and astronaut selected as the first private citizen to fly in space.
-
B.
Alexina Sattler
Alexina Sattler, better known as Alexina Duchamp, was the second wife and close companion of artist Marcel Duchamp, noted for her role in preserving and promoting his legacy.
-
C.
Therese
Therese is a feminine given name of French origin, commonly associated with Christian saints and used in various European cultures.
-
D.
Ricarda
Ricarda is a feminine given name, primarily used in German- and Spanish-speaking countries, derived from the male name Richard.
-
E.
Luisa
Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
- 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_69d85ccf2794819096cda4cbcb02d478 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e997ce481909b2f10d25705fbc6 |
completed | April 16, 2026, 2:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff5f3b643c819093230df6cfe440b9 |
completed | May 9, 2026, 4:22 p.m. |
Created at: April 10, 2026, 4:13 a.m.