Triple
T37729782
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Professor Thorton |
E940123
|
entity |
| Predicate | worksOnCharacter |
P60552
|
FINISHED |
| Object | Wolverine |
—
|
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: Wolverine | Statement: [Professor Thorton, worksOnCharacter, Wolverine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: worksOnCharacter Context triple: [Professor Thorton, worksOnCharacter, Wolverine]
-
A.
workedOnCharacter
chosen
Indicates that an entity contributed effort or labor to developing, portraying, or otherwise engaging with a particular character.
-
B.
worksUnderCharacter
Indicates that one character is hierarchically subordinate to another and performs their duties under that character’s authority or supervision.
-
C.
workCharacter
Indicates that a person is a fictional or narrative character appearing in a particular creative work.
-
D.
collaboratesWithCharacter
Indicates that one character works together with another character toward a shared goal or activity.
-
E.
appliesToCharacter
Indicates that an action, rule, or property is specifically directed toward or relevant for a particular character.
- 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_69f76edefd048190a32212c5c3919531 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fd0d0ba5c48190bddb3f0e6637544c |
completed | May 7, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69fd0c4324a8819086c90adf46216e0e |
completed | May 7, 2026, 10:03 p.m. |
Created at: May 3, 2026, 4:18 p.m.