Triple
T3818912
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aunt Bee Taylor |
E84323
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Beatrice |
E135226
|
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: Beatrice | Statement: [Aunt Bee Taylor, givenName, Beatrice]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beatrice Context triple: [Aunt Bee Taylor, givenName, Beatrice]
-
A.
Beatrice
Beatrice is the idealized woman in Dante Alighieri’s Divine Comedy who serves as his spiritual guide through Paradise and symbolizes divine love and theology.
-
B.
Beatrice
chosen
Beatrice is a feminine given name of Latin origin, traditionally associated with meanings like "she who brings happiness" or "bringer of joy."
-
C.
Bianca
Bianca is a key supporting character in the "Creed" film series, a musician and love interest of Adonis Creed who plays a central role in his personal life and emotional journey.
-
D.
Bianca
Bianca is a courtesan in Shakespeare’s tragedy "Othello," romantically involved with Cassio and used as a pawn in Iago’s schemes.
-
E.
Bianca
Bianca is a sophisticated and brave Hungarian mouse who serves as one of the heroic Rescue Aid Society agents in Disney’s animated films "The Rescuers" and its sequel.
- 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_69aed931f5908190be2c07af66d4df25 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeea601d408190b09dc486e77488d4 |
completed | March 9, 2026, 3:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4fb466a108190ac203ee00ce58f04 |
completed | March 14, 2026, 6:08 a.m. |
Created at: March 9, 2026, 3:17 p.m.