Triple
T29137122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avatar: The Last Airbender (2024 live-action series) |
E738536
|
entity |
| Predicate | featuresElementBending |
P119494
|
FINISHED |
| Object | waterbending |
—
|
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: waterbending | Statement: [Avatar: The Last Airbender (2024 live-action series), featuresElementBending, waterbending]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresElementBending Context triple: [Avatar: The Last Airbender (2024 live-action series), featuresElementBending, waterbending]
-
A.
bendingSubskill
Indicates a specific skill or technique that forms part of the broader ability to bend or flex something.
-
B.
bendAngle
Indicates the degree to which one part is bent relative to another, typically measured as the angle formed at their joint or intersection.
-
C.
featuresElementSystem
Indicates that a system includes or incorporates a particular element as one of its constituent parts or components.
-
D.
bendingStyle
chosen
Indicates the manner or technique by which something is bent or flexed.
-
E.
hasBulge
Indicates that one entity possesses or exhibits a protruding or swollen part relative to its surrounding surface or structure.
- 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_69f07cb3adb48190a9e0e169cd026634 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69ff1e3e13c08190bb8990c44716b746 |
completed | May 9, 2026, 11:45 a.m. |
| PD | Predicate disambiguation | batch_69ff1dfcaf2c8190aaf2b428d57b7782 |
completed | May 9, 2026, 11:43 a.m. |
Created at: April 28, 2026, 11:35 a.m.