Triple
T33723587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nadia Hilker |
E864081
|
entity |
| Predicate | portraysCharacterIn |
P198531
|
FINISHED |
| Object | Luna 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: Luna in The 100 | Statement: [Nadia Hilker, portraysCharacterIn, Luna in The 100]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysCharacterIn Context triple: [Nadia Hilker, portraysCharacterIn, Luna in The 100]
-
A.
portraysCharacterInGenre
Indicates that an entity depicts or plays a character within works belonging to a specified genre.
-
B.
portrayedVia
Indicates that one entity is represented, depicted, or expressed through a particular medium, method, or channel.
-
C.
directorPortraysCharacter
Indicates that a film director personally appears in a work portraying a specific character.
-
D.
portraysActorAs
Indicates that one entity depicts or represents an actor in a particular role, character, or manner.
-
E.
portraysMainCharacter
Indicates that one entity depicts or represents another entity as the primary or central character in a work or narrative.
- 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_69f34989871c81908682e22a2fe4b829 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fef112398081909237c3872345968b |
completed | May 9, 2026, 8:32 a.m. |
| PD | Predicate disambiguation | batch_69feefb14ec08190ab401987d8c84a23 |
completed | May 9, 2026, 8:26 a.m. |
| PDg | Predicate description generation | batch_69fef1112b0c8190a8eb027edb71e4e0 |
completed | May 9, 2026, 8:32 a.m. |
Created at: May 1, 2026, 1:44 a.m.