Triple
T36785838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NSEA Protector |
E908908
|
entity |
| Predicate | hasScienceOfficerPortrayedBy |
P81663
|
FINISHED |
| Object | Alexander Dane |
—
|
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: Alexander Dane | Statement: [NSEA Protector, hasScienceOfficerPortrayedBy, Alexander Dane]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasScienceOfficerPortrayedBy Context triple: [NSEA Protector, hasScienceOfficerPortrayedBy, Alexander Dane]
-
A.
hasHumanScientistCharacter
Indicates that an entity includes or features a character who is a human scientist.
-
B.
scienceOfficer
chosen
Indicates that one entity serves in the role or capacity of a science officer in relation to another entity.
-
C.
professorPortrayedBy
Indicates that a professor character is depicted or played by a specific person in a work (e.g., film, TV, or other media).
-
D.
wasPortrayedAs
Indicates that one entity has been depicted or represented in the form or role of another entity, typically within some medium or context.
-
E.
hasPortrayedPersonRole
Indicates that an entity has performed or held a specific role in portraying a particular person (e.g., in a film, play, or other representation).
- 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_69f76e7a937c81909ed7359641e670f6 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fd6f9d600c8190acf495b7fc632e4b |
completed | May 8, 2026, 5:07 a.m. |
| PD | Predicate disambiguation | batch_69fd6e98a2948190a9f78c415ad23b8c |
completed | May 8, 2026, 5:03 a.m. |
Created at: May 3, 2026, 4:12 p.m.