Triple
T8847741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Darci Kistler |
E210549
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Darci |
E514959
|
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: Darci | Statement: [Darci Kistler, givenName, Darci]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Darci Context triple: [Darci Kistler, givenName, Darci]
-
A.
Darcie
chosen
Darcie is a given name commonly used as a feminine first name in English-speaking countries.
-
B.
Danna
Danna is the surname of Mychael Danna, a Canadian composer renowned for his innovative and atmospheric film scores.
-
C.
Danielle
Danielle is the given first name of American actress and producer Riley Keough, known for her roles in films like "Mad Max: Fury Road" and the series "Daisy Jones & The Six."
-
D.
Danielle
"Danielle" is a work created by Sarah Churchill, known as part of her contributions to the arts.
-
E.
Danielle
Danielle is the young prodigy and central superheroine of the novel "Chronicles of a Superheroine," known for using her intelligence and creativity to tackle global challenges.
- 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_69ca838967bc8190b46c3c80a2887ea4 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc60a9194c8190bdfefc55a8fb29a3 |
completed | April 1, 2026, 12:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf89bd3ef48190a6a2efff18db4dbd |
completed | April 3, 2026, 9:34 a.m. |
Created at: March 30, 2026, 6:49 p.m.