Triple
T28065655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Verdello |
E709241
|
entity |
| Predicate | contributesCharacter |
P180860
|
FINISHED |
| Object | fresh character |
—
|
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: fresh character | Statement: [Verdello, contributesCharacter, fresh character]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: contributesCharacter Context triple: [Verdello, contributesCharacter, fresh character]
-
A.
characterIn
Indicates that an entity appears as a character within a specified work, story, or narrative.
-
B.
character2
Indicates that a second character entity is involved in the relationship or context defined by the predicate.
-
C.
character1
Indicates that the subject is identified as the first or primary character in a narrative or context.
-
D.
allyOfCharacter
Indicates that one character maintains an alliance or supportive partnership with another character.
-
E.
featuresCharacterWith
Indicates that one entity (such as a work or product) includes or presents a particular character as part of its content.
- 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_69ef9b6eb6d88190a3fea236eb0f7bed |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69f757898fe48190b124dc7301672623 |
completed | May 3, 2026, 2:11 p.m. |
| PD | Predicate disambiguation | batch_69f754c484348190948d2a04ff228fb1 |
completed | May 3, 2026, 1:59 p.m. |
| PDg | Predicate description generation | batch_69f75788d40c819083bf2567b3091585 |
completed | May 3, 2026, 2:11 p.m. |
Created at: April 27, 2026, 8:42 p.m.