Triple
T5434885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Principal Nathan Gardner |
E121983
|
entity |
| Predicate | isAdultCharacter |
P64043
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Principal Nathan Gardner, isAdultCharacter, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isAdultCharacter Context triple: [Principal Nathan Gardner, isAdultCharacter, true]
-
A.
hasAdultRank
Indicates that an entity holds a status or position classified as an adult-level rank within a given system or hierarchy.
-
B.
isMaleCharacter
Indicates that the referenced character is identified as male.
-
C.
containsAdultContent
Indicates that the referenced item includes material intended for adults, such as explicit sexual, violent, or otherwise age-restricted content.
-
D.
isHuman
Indicates that the subject entity possesses the defining characteristics or status of being a human.
-
E.
containsAge
Indicates that one entity includes or specifies the age value or age-related information of another entity.
- F. None of above. chosen
Provenance (4 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_69bd46400768819092925d461c0b8432 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd922f66bc8190b7d47fd68d2fcf2e |
completed | March 20, 2026, 6:30 p.m. |
| PD | Predicate disambiguation | batch_69bd919aeb048190b786f814177d6cd9 |
completed | March 20, 2026, 6:27 p.m. |
| PDg | Predicate description generation | batch_69bd922dc688819092bf33589ebc6d50 |
completed | March 20, 2026, 6:30 p.m. |
Created at: March 20, 2026, 2:06 p.m.