Triple
T27811796
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pym Technologies |
E702535
|
entity |
| Predicate | basedOnCharacterCreationOf |
P15277
|
FINISHED |
| Object | Hank Pym |
—
|
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: Hank Pym | Statement: [Pym Technologies, basedOnCharacterCreationOf, Hank Pym]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basedOnCharacterCreationOf Context triple: [Pym Technologies, basedOnCharacterCreationOf, Hank Pym]
-
A.
basedOnCharacterBy
chosen
Indicates that one work, adaptation, or portrayal is derived from or inspired by a character created by another entity.
-
B.
characterBasedOn
Indicates that one character is modeled, inspired, or derived from another real or fictional entity.
-
C.
basedOnCharacterOrigin
Indicates that one entity is derived from, inspired by, or determined according to the origin or background of a character.
-
D.
basedOnCharacterFromWork
Indicates that one entity is derived from, inspired by, or modeled after a character that appears in another creative work.
-
E.
basedOnCharacterOccupation
Indicates that something is derived from, inspired by, or determined according to a character’s occupation or job role.
- 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_69ef840a16748190926719ab96120bae |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f78fd5a6388190bfda4bbb2e222e5b |
completed | May 3, 2026, 6:11 p.m. |
| PD | Predicate disambiguation | batch_69f78e2ac3fc819081a45c6841375c8d |
completed | May 3, 2026, 6:04 p.m. |
Created at: April 27, 2026, 5:43 p.m.