Triple
T35548985
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Don’t Worry, I’m Fine |
E1027299
|
entity |
| Predicate | hasTwinSiblingOfProtagonist |
P165578
|
FINISHED |
| Object | Lili’s twin brother |
—
|
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: Lili’s twin brother | Statement: [Don’t Worry, I’m Fine, hasTwinSiblingOfProtagonist, Lili’s twin brother]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTwinSiblingOfProtagonist Context triple: [Don’t Worry, I’m Fine, hasTwinSiblingOfProtagonist, Lili’s twin brother]
-
A.
hasTwin
Indicates that one entity is a twin of another, sharing the same birth event or time with a sibling.
-
B.
isBrotherOfProtagonist
chosen
Indicates that one person is the male sibling of the story’s main character.
-
C.
hasSisterProtagonists
Indicates that the work features two or more main characters who are sisters as its central protagonists.
-
D.
isFictionalTwinOf
Indicates that one entity is the imagined or fictional twin counterpart of another entity, typically within a narrative or creative context.
-
E.
hasFictionalSibling
Indicates that one entity is a fictional character who is a sibling of another entity.
- 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_69f76e008ba08190927acd8e5e0344c8 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79a54aa3c8190b2bb5d790b2d42d4 |
completed | May 3, 2026, 6:56 p.m. |
| PD | Predicate disambiguation | batch_69f7961970408190b669cc556e30a608 |
completed | May 3, 2026, 6:38 p.m. |
Created at: May 3, 2026, 4:04 p.m.