Triple
T38396983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Astrid Lindgren’s World |
E900788
|
entity |
| Predicate | hasCharacterArea |
P111069
|
FINISHED |
| Object | Pippi Longstocking |
—
|
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: Pippi Longstocking | Statement: [Astrid Lindgren’s World, hasCharacterArea, Pippi Longstocking]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCharacterArea Context triple: [Astrid Lindgren’s World, hasCharacterArea, Pippi Longstocking]
-
A.
hasInnerAreaCharacter
Indicates that an entity possesses a specific characteristic or quality related to its inner area or interior region.
-
B.
hasCharacters
chosen
Indicates that an entity (such as a work or story) includes or features certain characters as part of its content.
-
C.
hasBorderAreaCharacteristics
Indicates that something possesses features or qualities typical of a border area between regions or territories.
-
D.
hasCharacterPresence
Indicates that a particular character appears or is present within a specified context, such as a scene, work, or medium.
-
E.
hasCharacterContext
Indicates that a character is associated with or participates in a particular contextual situation, setting, or state.
- 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_69f76e6071a081909eea7a670d21420c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ff5803c02c81908b63067119f5e684 |
completed | May 9, 2026, 3:51 p.m. |
| PD | Predicate disambiguation | batch_69ff576d8b308190b49a1e072a0ae661 |
completed | May 9, 2026, 3:49 p.m. |
Created at: May 3, 2026, 4:31 p.m.