Triple
T30734881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Neighbor (2018 film) |
E782524
|
entity |
| Predicate | hasNeighborCharacters |
P127491
|
FINISHED |
| Object | mysterious couple |
—
|
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: mysterious couple | Statement: [The Neighbor (2018 film), hasNeighborCharacters, mysterious couple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNeighborCharacters Context triple: [The Neighbor (2018 film), hasNeighborCharacters, mysterious couple]
-
A.
hasNeighborCharacter
chosen
Indicates that one character is directly adjacent to another character in a sequence or arrangement.
-
B.
hasSiblingCharacters
Indicates that two characters share at least one common parent, making them siblings in the narrative or data context.
-
C.
hasCharacters
Indicates that an entity (such as a work or story) includes or features certain characters as part of its content.
-
D.
surroundingCharacter
Indicates that one character is located around or encircling another character or element in the context of a layout or structure.
-
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_69f224aeb1588190897d395e8ed2acb8 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69feb5e66224819083b87c3707a5a5e0 |
completed | May 9, 2026, 4:19 a.m. |
| PD | Predicate disambiguation | batch_69feb3bd700c8190991ed200cd3c04db |
completed | May 9, 2026, 4:10 a.m. |
Created at: April 29, 2026, 8:37 p.m.