Triple
T35162750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harmon House |
E1015311
|
entity |
| Predicate | causesToCharacters |
P87321
|
FINISHED |
| Object | psychological terror |
—
|
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: psychological terror | Statement: [Harmon House, causesToCharacters, psychological terror]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: causesToCharacters Context triple: [Harmon House, causesToCharacters, psychological terror]
-
A.
causedByCharacter
Indicates that an event, state, or outcome occurs as a direct result of the actions or influence of a specific character.
-
B.
givenToCharacter
Indicates that something (such as an item, gift, or resource) has been transferred or presented to a particular character.
-
C.
characters
Indicates that one entity is a character (or set of characters) associated with, appearing in, or belonging to another entity (such as a work, story, or medium).
-
D.
plotCharacter
Indicates a relationship where a character plays a role or participates in the narrative plot of a story or work.
-
E.
targetsCharacter
chosen
Indicates that one entity is the intended focus or target of another entity’s action, effect, or behavior.
- 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_69f76ddbfde081908bffc91572368289 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fd32848ea88190a71e6df402bbb30e |
completed | May 8, 2026, 12:47 a.m. |
| PD | Predicate disambiguation | batch_69fd2d7e95588190991d5f21e25155df |
completed | May 8, 2026, 12:25 a.m. |
Created at: May 3, 2026, 4:02 p.m.