Triple
T14551989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Margaret Thatcher in The Crown |
E341439
|
entity |
| Predicate | accentDepiction |
P29850
|
FINISHED |
| Object | distinctive Thatcherite vocal style |
—
|
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: distinctive Thatcherite vocal style | Statement: [Margaret Thatcher in The Crown, accentDepiction, distinctive Thatcherite vocal style]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: accentDepiction Context triple: [Margaret Thatcher in The Crown, accentDepiction, distinctive Thatcherite vocal style]
-
A.
voiceActorAccent
Indicates that a voice actor performs their role using a specified accent.
-
B.
vocalizationCharacteristic
chosen
Indicates how an entity’s vocal sounds are characterized, such as their quality, style, or distinctive acoustic features.
-
C.
typeOfPronunciationDescribed
Indicates that one entity specifies or characterizes the kind or style of pronunciation associated with another entity.
-
D.
depictsSound
Indicates that one entity visually represents or portrays the sound produced by another entity.
-
E.
speakerFeatures
Indicates that certain characteristics, attributes, or properties are associated with a speaker in a given context.
- 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_69d822db9c8481908213ceb39585f792 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb2ee34208190bf040a513767c958 |
completed | April 14, 2026, 9:34 p.m. |
| PD | Predicate disambiguation | batch_69de5c546c7081909e27d504ec360c5c |
completed | April 14, 2026, 3:25 p.m. |
Created at: April 10, 2026, 1:23 a.m.