Triple
T20890606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grace Slick |
E514397
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Grace |
—
|
NE NERFINISHED |
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: Grace | Statement: [Grace Slick, givenName, Grace]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grace Context triple: [Grace Slick, givenName, Grace]
-
A.
Grace
chosen
Grace is the central Christian concept of God’s unmerited favor and loving initiative toward humanity, enabling salvation and spiritual transformation.
-
B.
Grace
Grace is a cybernetically enhanced human soldier from the future who serves as one of the main protagonists in the film "Terminator: Dark Fate."
-
C.
Grace
"Grace" is a single from the album "Self-Titled," known for its emotive style and central role in defining the artist’s sound on that record.
-
D.
Grace
Grace is a 2017 studio album by American jazz and gospel-influenced singer Lizz Wright that blends soul, folk, and spirituals into a reflective, rootsy collection.
-
E.
Grace
Grace is a supporting character in the television series "Dr. Quinn, Medicine Woman," known as the town's skilled and compassionate café owner and cook.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4f7ebe48190952a85547a0f31a1 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6d05e307081908f1d044e877017ec |
completed | April 21, 2026, 1:18 a.m. |
Created at: April 16, 2026, 12:46 p.m.