Triple
T20939811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Isaac |
E515687
|
entity |
| Predicate | mother |
P120
|
FINISHED |
| Object | Sarah |
—
|
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: Sarah | Statement: [Isaac, mother, Sarah]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sarah Context triple: [Isaac, mother, Sarah]
-
A.
Sarah
Sarah is the central protagonist of the story "Horse Girl," around whom the main narrative and character development revolve.
-
B.
Sarah
Sarah is a person whose full name is Sarah Catherine McPherson Risher Getty.
-
C.
Sarah
Sarah is the given name of Sarah P. Duke, the philanthropist and namesake of Duke University's Sarah P. Duke Gardens.
-
D.
Sarah
Sarah is the given name of the renowned 19th- and early 20th-century French stage actress Sarah Bernhardt, often called "the Divine Sarah."
-
E.
Sarah
Sarah Onyango Obama was the Kenyan educator and philanthropist best known as the step-grandmother of former U.S. President Barack Obama.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69e0b4fc13408190b06868df03c5c29b |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6f954e44481909098a0b23a687d5e |
completed | April 21, 2026, 4:13 a.m. |
Created at: April 16, 2026, 12:50 p.m.