Triple
T27471367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adelaide Brooke |
E693327
|
entity |
| Predicate | encountersDoctor |
P162421
|
FINISHED |
| Object | Tenth Doctor |
—
|
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: Tenth Doctor | Statement: [Adelaide Brooke, encountersDoctor, Tenth Doctor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: encountersDoctor Context triple: [Adelaide Brooke, encountersDoctor, Tenth Doctor]
-
A.
reasonForVisits
Indicates the underlying cause, purpose, or motivation that explains why a visit or set of visits occurred.
-
B.
examinedIn
Indicates that one entity is analyzed, inspected, or studied within the context, scope, or setting provided by another entity.
-
C.
doctorNumber
Indicates the unique identifying number assigned to a doctor in the context of a relationship or record.
-
D.
hasDoctorActor
Indicates that a doctor participates as an acting agent in the specified event or relationship.
-
E.
medicalEvent
Indicates that a specific health-related occurrence or clinical incident has taken place involving one or more entities.
- F. None of above. chosen
Provenance (4 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_69ef538105548190a771cc5a0cf8c211 |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69f62e01958c8190925c7f71b0ba0150 |
completed | May 2, 2026, 5:01 p.m. |
| PD | Predicate disambiguation | batch_69f623aaf40081909f947431424a1d55 |
completed | May 2, 2026, 4:17 p.m. |
| PDg | Predicate description generation | batch_69f624c006788190a2f4d5015c96463f |
completed | May 2, 2026, 4:22 p.m. |
Created at: April 27, 2026, 12:54 p.m.