Triple
T12420338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sybil Thorndike |
E296751
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Agnes |
E88099
|
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: Agnes | Statement: [Sybil Thorndike, givenName, Agnes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Agnes Context triple: [Sybil Thorndike, givenName, Agnes]
-
A.
Agnes
chosen
Agnes is a feminine given name of Greek origin meaning "pure" or "chaste," historically popular in various European cultures and Christian traditions.
-
B.
Agnes
Agnes is the sweet, unicorn-obsessed youngest daughter of Gru in the Despicable Me franchise, known for her innocence, enthusiasm, and iconic “It’s so fluffy!” line.
-
C.
Agnes
Agnes is a character from Matthew Gregory Lewis's Gothic novel "The Monk," known for her tragic storyline involving forbidden love and persecution.
-
D.
Agnes
Agnes is a young nun at the center of a psychological and spiritual mystery surrounding a newborn's death in the play and film "Agnes of God."
-
E.
Agnes
Agnes is the devout young heroine of Harriet Beecher Stowe’s novel "Agnes of Sorrento," set in Renaissance Italy.
- 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_69d6ada0640c81908c061d7fb3d47786 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94d6efd748190a5d9396a343e41e1 |
completed | April 10, 2026, 7:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f634933b9881909fd592ede7c3e49c |
completed | May 2, 2026, 5:29 p.m. |
Created at: April 8, 2026, 9:55 p.m.