Triple
T15158582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Hartnell |
E362146
|
entity |
| Predicate | firstAppearanceAsTheDoctorDate |
P113682
|
FINISHED |
| Object | 1963-11-23 |
—
|
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: 1963-11-23 | Statement: [William Hartnell, firstAppearanceAsTheDoctorDate, 1963-11-23]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstAppearanceAsTheDoctorDate Context triple: [William Hartnell, firstAppearanceAsTheDoctorDate, 1963-11-23]
-
A.
firstAppearedWithDoctor
Indicates the specific Doctor character with whom an entity (such as a companion, monster, or concept) made its first appearance.
-
B.
airDateOfFirstAppearance
chosen
Indicates the calendar date on which an entity (such as a character, show, or episode) was first broadcast or made publicly available.
-
C.
firstPublicationYearOfAppearance
Indicates the year in which an entity (such as a work or character) first appeared in a published form.
-
D.
firstAppearanceApprox
Indicates that one entity is the approximate or estimated first appearance of another entity in time or context.
-
E.
firstAppearanceTV
Indicates the television show or episode in which an entity is depicted or mentioned for the first time.
- 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_69d85a0759908190b8a051d2e2a1cbe6 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0060dd71881908ecc4a4f52d438a5 |
completed | April 15, 2026, 9:41 p.m. |
| PD | Predicate disambiguation | batch_69deb9779acc81908ed2dad382c42dca |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:08 a.m.