Triple
T36265470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. McBrearty |
E892208
|
entity |
| Predicate | responsibleFor |
P636
|
FINISHED |
| Object |
medically assessing Anna O’Donnell
Medically assessing Anna O’Donnell is the clinical evaluation and monitoring of the young fasting girl at the center of Emma Donoghue’s novel *The Wonder*, undertaken to determine her true health and the authenticity of her supposed miracle fast.
|
E2176000
|
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: medically assessing Anna O’Donnell | Statement: [Dr. McBrearty, responsibleFor, medically assessing Anna O’Donnell]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: medically assessing Anna O’Donnell Triple: [Dr. McBrearty, responsibleFor, medically assessing Anna O’Donnell]
Generated description
Medically assessing Anna O’Donnell is the clinical evaluation and monitoring of the young fasting girl at the center of Emma Donoghue’s novel *The Wonder*, undertaken to determine her true health and the authenticity of her supposed miracle fast.
Provenance (5 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_69f76e4699188190af045b11a840ce31 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b6267e488190bbebcd8b4acc7e1b |
completed | May 3, 2026, 8:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a396e0c50508190953c4b30f6dc227e |
completed | June 22, 2026, 5:17 p.m. |
| NEDg | Description generation | batch_6a396ea572248190986c4f71d6cde887 |
completed | June 22, 2026, 5:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a396f3ec8bc8190b9f3a25381b8a52d |
completed | June 22, 2026, 5:22 p.m. |
Created at: May 3, 2026, 4:09 p.m.