Triple
T32614135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Journey into Mystery #83 |
E833739
|
entity |
| Predicate | hasBackupStories |
P190372
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Journey into Mystery #83, hasBackupStories, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBackupStories Context triple: [Journey into Mystery #83, hasBackupStories, yes]
-
A.
hasFlashbackStorylines
Indicates that the narrative includes scenes or sequences set in earlier time periods that reveal past events related to the main storyline.
-
B.
hasSiblingInStory
Indicates that one character in a narrative has at least one sibling who also appears within the same story.
-
C.
hasVariantStoriesIn
Indicates that an entity has alternative or differing narrative versions that occur or are found within a specified context or source.
-
D.
hasOriginalStory
Indicates that one entity serves as the original narrative source or story upon which the other entity is based or derived.
-
E.
hasInfluentialStory
Indicates that one entity possesses or is associated with a story that significantly shapes, impacts, or guides the beliefs, actions, or development 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_69f3492bfa648190b6ae472074634e29 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fcc4b700748190ae00b21d09c96695 |
completed | May 7, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69fcb0f9d3d881908a049475182fb039 |
completed | May 7, 2026, 3:34 p.m. |
| PDg | Predicate description generation | batch_69fcc4b5f22c8190b8b256adbdc2570c |
completed | May 7, 2026, 4:58 p.m. |
Created at: May 1, 2026, 1:06 a.m.