Triple
T4390597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Can You Say... Hero? |
E99350
|
entity |
| Predicate | originallyAppearedAs |
P21112
|
FINISHED |
| Object | Esquire feature story |
—
|
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: Esquire feature story | Statement: [Can You Say... Hero?, originallyAppearedAs, Esquire feature story]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originallyAppearedAs Context triple: [Can You Say... Hero?, originallyAppearedAs, Esquire feature story]
-
A.
firstAppeared
Indicates the earliest known time or context in which an entity was introduced, observed, or came into existence.
-
B.
firstAppearanceFor
Indicates that an entity marks the initial occurrence or debut of another entity within a given context or medium.
-
C.
firstReleasedAs
chosen
Indicates the original title or form under which an entity (such as a work, product, or version) was initially released before any later re-releases, renamings, or editions.
-
D.
originallyAiredAs
Indicates that one work or episode was first broadcast under a particular title, format, or context.
-
E.
firstAppearedAt
Indicates the point in time or specific event at which an entity was first introduced, observed, or became known.
- 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_69b3454f739481909ff6c28331f0c0b9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b352843d7c8190929b94c94eaa63df |
completed | March 12, 2026, 11:55 p.m. |
| PD | Predicate disambiguation | batch_69b34f572efc8190bad1e5078cbcb75a |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:19 p.m.