Triple
T36540341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doctor Who: Relative Dimensions (audio drama) |
E900702
|
entity |
| Predicate | featuresDoctorNumber |
P50208
|
FINISHED |
| Object | 8 |
—
|
LITERAL 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: 8 | Statement: [Doctor Who: Relative Dimensions (audio drama), featuresDoctorNumber, 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresDoctorNumber Context triple: [Doctor Who: Relative Dimensions (audio drama), featuresDoctorNumber, 8]
-
A.
doctorNumber
chosen
Indicates the unique identifying number assigned to a doctor in the context of a relationship or record.
-
B.
featuredDoctor
Indicates that a particular doctor is highlighted or promoted as a primary or notable medical professional in a given context.
-
C.
mainDoctor
Indicates that one entity serves as the primary or responsible doctor for another entity (such as a patient or medical case).
-
D.
hasDoctorActor
Indicates that a doctor participates as an acting agent in the specified event or relationship.
-
E.
doctor
Indicates that one entity serves as a medical professional providing diagnosis, treatment, or healthcare services to another entity.
- F. None of above.
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_69f76e5fbb388190b70c4c15573c8143 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0bf4b88190bdcfae9a14b51f0a |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:11 p.m.