Triple
T15158590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Hartnell |
E362146
|
entity |
| Predicate | typeOfDoctorWhoActor |
P16411
|
FINISHED |
| Object | original lead actor |
—
|
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: original lead actor | Statement: [William Hartnell, typeOfDoctorWhoActor, original lead actor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfDoctorWhoActor Context triple: [William Hartnell, typeOfDoctorWhoActor, original lead actor]
-
A.
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).
-
B.
featuresIncarnationOfDoctor
Indicates that the subject includes or presents a specific incarnation (version) of the Doctor character.
-
C.
typeOfCharacter
Indicates that one entity is a specific kind or category of character in relation to another entity.
-
D.
playedBy
Indicates that a role, character, or performance is portrayed or executed by a specific person or agent.
-
E.
actingRoleType
chosen
Indicates the specific type or category of role an entity performs when acting in a particular capacity or function.
- 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.