Triple
T35221040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joanne Siegel |
E1016953
|
entity |
| Predicate | metJerrySiegelWhen |
P182626
|
FINISHED |
| Object | as a teenage model posing for Lois Lane |
—
|
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: as a teenage model posing for Lois Lane | Statement: [Joanne Siegel, metJerrySiegelWhen, as a teenage model posing for Lois Lane]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: metJerrySiegelWhen Context triple: [Joanne Siegel, metJerrySiegelWhen, as a teenage model posing for Lois Lane]
-
A.
creatorInComics
Indicates that one entity is the creator (such as writer or artist) responsible for the content or characters appearing in a particular comic work or series.
-
B.
comicStripDebutYear
Indicates the year in which a comic strip was first published or debuted.
-
C.
Jack Hively
Indicates a relationship or action involving the person named Jack Hively, such as authorship, direction, or participation in a work or event.
-
D.
roleInComics
Indicates that an entity holds a specific role or function within the context of comic books or comic-related works.
-
E.
creatorOfCharacter
Indicates that one entity is the originator or author who created or conceived the other entity as a character.
- 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_69f76de072908190ab65038a8a7b6a79 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f7904a770481908ef3f788e51e8dba |
completed | May 3, 2026, 6:13 p.m. |
| PD | Predicate disambiguation | batch_69f78e2d71248190b850c2802ec170c0 |
completed | May 3, 2026, 6:04 p.m. |
| PDg | Predicate description generation | batch_69f78f629d508190b755848162c4e101 |
completed | May 3, 2026, 6:09 p.m. |
Created at: May 3, 2026, 4:02 p.m.