Triple
T7451560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Let Love Rule |
E172019
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Fear |
E343298
|
NE 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: Fear | Statement: [Let Love Rule, hasPart, Fear]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fear Context triple: [Let Love Rule, hasPart, Fear]
-
A.
Fear
Fear is a nervous, cautious emotion character in Pixar's animated film "Inside Out," responsible for keeping Riley safe by anticipating potential dangers.
-
B.
Fear
chosen
"Fear" is a song by American rock band Blue October, known for its introspective lyrics and emotional exploration of anxiety and overcoming inner struggles.
-
C.
Fearing
Fearing is a given name most notably associated with Rufus Fearing Dawes, an American Civil War officer and politician.
-
D.
Fear Factor
Fear Factor is a reality television game show in which contestants compete in extreme and often fear-inducing stunts for cash prizes.
-
E.
Dread
Dread is a British science fiction horror film known for its psychological intensity and adaptation of a Clive Barker short story.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c68a66554c8190add75c65942c0317 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f38c28e08190956766a5222fe720 |
completed | March 27, 2026, 9:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c827b54a4881909f800bf37990a297 |
completed | March 28, 2026, 7:10 p.m. |
Created at: March 27, 2026, 3:14 p.m.