Triple
T20700478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samson and Delilah (1949 film score) |
E508765
|
entity |
| Predicate | settingOfMusic |
P60537
|
FINISHED |
| Object | ancient Israel |
—
|
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: ancient Israel | Statement: [Samson and Delilah (1949 film score), settingOfMusic, ancient Israel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingOfMusic Context triple: [Samson and Delilah (1949 film score), settingOfMusic, ancient Israel]
-
A.
settingInMusical
chosen
Indicates that one entity serves as the setting or location in which the events of a musical take place.
-
B.
setToMusicAs
Indicates that one entity (typically a text or work) has been adapted and arranged by another entity into a musical composition.
-
C.
hasMusicalSettingsBy
Indicates that a work has been set to music or musically arranged by a specified creator or composer.
-
D.
setToMusicIn
Indicates that something (typically text or lyrics) has been arranged or adapted to be performed as music within a particular work or context.
-
E.
regulatesMusic
Indicates that one entity controls, governs, or sets rules for another entity’s music-related activities or outputs.
- 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_69e0b4c2b2a481909e31e9cb8f81ab55 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6c18a77308190b7c2517d82a145cd |
completed | April 21, 2026, 12:15 a.m. |
| PD | Predicate disambiguation | batch_69e5c044d1108190b2b5d25de23f6401 |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 12:12 p.m.