Triple
T37529549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Flash |
E932992
|
entity |
| Predicate | hasLegacyCharacters |
P129156
|
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: [The Flash, hasLegacyCharacters, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLegacyCharacters Context triple: [The Flash, hasLegacyCharacters, true]
-
A.
isLegacyCharacterFor
chosen
Indicates that one entity is an older, previously established character associated with or originating from the context, storyline, or franchise of another entity.
-
B.
hasLegacy
Indicates that an entity leaves behind a lasting impact, influence, or inheritance that continues to exist or be recognized over time.
-
C.
containsHistoricCharacters
Indicates that something includes or features characters who are historically significant or based on real historical figures.
-
D.
hasHumanCharacters
Indicates that the subject includes or features characters that are human beings.
-
E.
hasTraditionalCharacter
Indicates that an entity is associated with or represented by a traditional (non-simplified or historically established) written character form.
- 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_69f76ec8862c8190bfa24145f5480642 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fe8ddf70e48190a917eb9e8f7b6966 |
completed | May 9, 2026, 1:29 a.m. |
| PD | Predicate disambiguation | batch_69fe87ef94dc81909bb00ec8d6de9bcd |
completed | May 9, 2026, 1:03 a.m. |
Created at: May 3, 2026, 4:17 p.m.