Triple
T35280038
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tales to Astonish #49 |
E1018908
|
entity |
| Predicate | featuresCharacterRealName |
P155411
|
FINISHED |
| Object | Henry Pym |
E64976
|
NE 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: Henry Pym | Statement: [Tales to Astonish #49, featuresCharacterRealName, Henry Pym]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresCharacterRealName Context triple: [Tales to Astonish #49, featuresCharacterRealName, Henry Pym]
-
A.
titleCharacterRealName
chosen
Indicates that a character known by a title or alias has the specified real (personal) name.
-
B.
characterFullName
Indicates that the predicate specifies the complete, formal name of a character.
-
C.
featuresCharacterWith
Indicates that one entity (such as a work or product) includes or presents a particular character as part of its content.
-
D.
featuresCharactersFrom
Indicates that one entity (such as a work or production) includes or presents characters originating from another entity.
-
E.
filmCharacterOf
Indicates that a person or character is a character appearing in a specified film.
- F. None of above.
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_69f76de6d39c8190bb11342e4b91ff2b |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3823b9225081908968e6650b362cf7 |
completed | June 21, 2026, 5:47 p.m. |
| PD | Predicate disambiguation | batch_6a037a0324d08190ac5b610cc0f6a38c |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:03 p.m.