Triple
T8666932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norman Wisdom comedies |
E205698
|
entity |
| Predicate | typicalProtagonistName |
P29319
|
FINISHED |
| Object | Norman Pitkin |
—
|
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: Norman Pitkin | Statement: [Norman Wisdom comedies, typicalProtagonistName, Norman Pitkin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalProtagonistName Context triple: [Norman Wisdom comedies, typicalProtagonistName, Norman Pitkin]
-
A.
mainProtagonist
Indicates that the subject is the central character or primary focus in the narrative of the related work.
-
B.
protagonistType
Indicates the role or category that the main character (protagonist) of a story or scenario belongs to.
-
C.
protagonistFullName
chosen
Indicates that the subject entity is the full, proper name (including given and family names) of the story’s main protagonist.
-
D.
protagonistIs
Indicates that one entity serves as the main character or central figure in relation to another entity or narrative context.
-
E.
protagonistDescription
Indicates that a text provides a descriptive summary or characterization of the story’s main protagonist.
- 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_69ca83516ae88190aefe034b3bc589e3 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc48a34b808190aa9aed9cdb2900e6 |
completed | March 31, 2026, 10:20 p.m. |
| PD | Predicate disambiguation | batch_69cc4564e018819081036722f3e42a71 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:31 p.m.