Triple
T26191929
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marie Avgeropoulos |
E654985
|
entity |
| Predicate | characterNameInWork |
P36851
|
FINISHED |
| Object | Octavia Blake in The 100 |
—
|
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: Octavia Blake in The 100 | Statement: [Marie Avgeropoulos, characterNameInWork, Octavia Blake in The 100]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterNameInWork Context triple: [Marie Avgeropoulos, characterNameInWork, Octavia Blake in The 100]
-
A.
characterName
chosen
Indicates that an entity has a specific name used to identify its character.
-
B.
characterInWorkDescribedAs
Indicates that a character is portrayed or described in a particular way within a specific work.
-
C.
characterIn
Indicates that an entity appears as a character within a specified work, story, or narrative.
-
D.
characterTitle
Indicates that a character holds or is associated with a specific title, rank, or formal designation.
-
E.
characterFullName
Indicates that the predicate specifies the complete, formal name of a 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_69ee5b469bc081908fe486453fdad810 |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f6bbf6e33c819086e5176d64e7a614 |
completed | May 3, 2026, 3:07 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6b1e6c8190adf9d6a257e0b744 |
completed | May 3, 2026, 3 a.m. |
Created at: April 26, 2026, 8:44 p.m.