Triple
T16790651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colin Baker |
E408099
|
entity |
| Predicate | doctorNumberInDoctorWho |
P50208
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [Colin Baker, doctorNumberInDoctorWho, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: doctorNumberInDoctorWho Context triple: [Colin Baker, doctorNumberInDoctorWho, 6]
-
A.
numberOfDoctorWhoNovelisations
Indicates the quantity of Doctor Who novelisations associated with a given subject.
-
B.
featuresIncarnationOfDoctor
Indicates that the subject includes or presents a specific incarnation (version) of the Doctor character.
-
C.
portrayedDoctorBy
Indicates that one entity served in the role of portraying a doctor character associated with another entity (such as a show, film, or franchise).
-
D.
firstAppearanceAsTheDoctor
Indicates the event or work in which an actor portrays the Doctor character for the first time.
-
E.
doctorNumber
chosen
Indicates the unique identifying number assigned to a doctor in the context of a relationship or record.
- 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_69d8839270588190886720d9519bbf8f |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b2a5d10c8190a581de79e4f7ccfa |
completed | April 18, 2026, 4:34 p.m. |
| PD | Predicate disambiguation | batch_69e319cf691c819083e39225f5777ef0 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:22 a.m.