Triple
T27065381
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elizabeth Henstridge |
E685158
|
entity |
| Predicate | portrayedScientist |
P1507
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Elizabeth Henstridge, portrayedScientist, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayedScientist Context triple: [Elizabeth Henstridge, portrayedScientist, true]
-
A.
professorPortrayedBy
Indicates that a professor character is depicted or played by a specific person in a work (e.g., film, TV, or other media).
-
B.
portrayedBy
chosen
Indicates that one entity serves as the actor or performer who represents or plays the role of another entity in a work or medium.
-
C.
portrayedArtist
Indicates that one entity has depicted or represented another entity as an artist in some medium or work.
-
D.
portrayedByAlsoPlays
Indicates that the actor who portrays a given character also plays another specified role or character.
-
E.
portrayedVia
Indicates that one entity is represented, depicted, or expressed through a particular medium, method, or channel.
- 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_69ef14835fcc81908bd737b4267ae528 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f7675b12848190a3569cfda29c5b0e |
completed | May 3, 2026, 3:18 p.m. |
| PD | Predicate disambiguation | batch_69f762f4b59481909f70074f11825bfb |
completed | May 3, 2026, 3 p.m. |
Created at: April 27, 2026, 8:24 a.m.