Triple
T4737553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eva Luna |
E105160
|
entity |
| Predicate | characterBackground |
P34184
|
FINISHED |
| Object | orphan |
—
|
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: orphan | Statement: [Eva Luna, characterBackground, orphan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterBackground Context triple: [Eva Luna, characterBackground, orphan]
-
A.
protagonistBackground
Indicates that one entity serves as the background, history, or prior circumstances of the protagonist entity in a narrative or story.
-
B.
characterOrigin
chosen
Indicates the source, background, or initial context from which a character originates.
-
C.
characterDescription
Indicates that one entity provides a textual description or portrayal of the characteristics, traits, or attributes of another entity.
-
D.
hasProtagonistBackground
Indicates that a work or narrative features a specified background or origin story for its main protagonist.
-
E.
character1
Indicates that the subject is identified as the first or primary character in a narrative or context.
- 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_69bd43ee52048190b81a4f066534ffb3 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd64844b7081909c9d36e4b461379e |
completed | March 20, 2026, 3:15 p.m. |
| PD | Predicate disambiguation | batch_69bd6221c3b881908604f35f8de6f16b |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:19 p.m.