Triple
T29149645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaa (Rudyard Kipling character) |
E738868
|
entity |
| Predicate | alignmentInOriginalWork |
P166556
|
FINISHED |
| Object | benevolent |
—
|
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: benevolent | Statement: [Kaa (Rudyard Kipling character), alignmentInOriginalWork, benevolent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alignmentInOriginalWork Context triple: [Kaa (Rudyard Kipling character), alignmentInOriginalWork, benevolent]
-
A.
originallyAlignedWith
Indicates that an entity was initially in agreement, support, or association with another entity or group, regardless of any later changes in stance or affiliation.
-
B.
alignmentInOriginalComics
Indicates the moral or factional stance a character holds in the original comic source material (e.g., hero, villain, neutral).
-
C.
alignmentInStory
Indicates how a character’s moral or ethical stance (e.g., good, neutral, evil) is portrayed within the context of a specific story.
-
D.
hasAlignmentInFiction
Indicates that a fictional character, group, or entity possesses a specific moral or ethical alignment within a fictional setting.
-
E.
alignmentAtIntroduction
Indicates that two entities share a particular alignment or stance at the moment one is first introduced.
- 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_69f07cb46f148190874eb8576a447567 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f662a439c88190985b014077e75ecc |
completed | May 2, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69f660f082508190a95a7888ad66cb2e |
completed | May 2, 2026, 8:39 p.m. |
| PDg | Predicate description generation | batch_69f6617a7e7c81908cfac4a2250797ee |
completed | May 2, 2026, 8:41 p.m. |
Created at: April 28, 2026, 11:41 a.m.