Triple
T29136798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katara |
E738529
|
entity |
| Predicate | learnedBloodbendingFrom |
P166358
|
FINISHED |
| Object | Hama |
—
|
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: Hama | Statement: [Katara, learnedBloodbendingFrom, Hama]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: learnedBloodbendingFrom Context triple: [Katara, learnedBloodbendingFrom, Hama]
-
A.
learnedIn
Indicates that an entity acquired knowledge, skills, or information within a particular context, environment, or source.
-
B.
learnsSkill
Indicates that an entity acquires or develops a particular skill through learning or practice.
-
C.
canBeLearnedBy
Indicates that a particular subject, skill, or knowledge is capable of being acquired or mastered by a specified learner or group of learners.
-
D.
learnedFromDemons
Indicates that an entity acquired knowledge, skills, or information through interaction or instruction from demons.
-
E.
hasBlackBeltIn
Indicates that an entity holds a black belt rank or equivalent high-level certification in a specified martial art or discipline.
- 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_69f07cb3adb48190a9e0e169cd026634 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f6626b8aa881908e1bf4776c2feea9 |
completed | May 2, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69f65c2376a08190be5215171e908e69 |
completed | May 2, 2026, 8:18 p.m. |
| PDg | Predicate description generation | batch_69f65f75ac608190a62cd6afce14f68e |
completed | May 2, 2026, 8:32 p.m. |
Created at: April 28, 2026, 11:34 a.m.