Triple
T9372268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uncle Albert/Admiral Halsey |
E225557
|
entity |
| Predicate | usesStudioEffects |
P88203
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Uncle Albert/Admiral Halsey, usesStudioEffects, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesStudioEffects Context triple: [Uncle Albert/Admiral Halsey, usesStudioEffects, true]
-
A.
specialEffectsBy
Indicates that the special effects for something (such as a film, scene, or shot) are created or provided by a particular person or entity.
-
B.
usesModulation
Indicates that one entity applies or employs a particular modulation method or scheme in relation to another entity or process.
-
C.
hasGuitarEffect
Indicates that one entity applies, uses, or is associated with a particular guitar effect in relation to another entity.
-
D.
usesAudioFrom
Indicates that one entity incorporates or relies on the audio content produced or provided by another entity.
-
E.
audioModulation
Indicates a relationship where one audio signal or parameter is used to vary or control another audio signal’s characteristics (such as amplitude, frequency, or timbre) over time.
- F. None of above. chosen
Provenance (4 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_69ca842cbddc819099d71ecec48cf9e5 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd50852a388190be936df1382216bc |
completed | April 1, 2026, 5:06 p.m. |
| PD | Predicate disambiguation | batch_69cc7a6abb8c81908c7a2f4ee92cc949 |
completed | April 1, 2026, 1:52 a.m. |
| PDg | Predicate description generation | batch_69cc955a38108190b602d1e73725f11b |
completed | April 1, 2026, 3:47 a.m. |
Created at: March 30, 2026, 7:43 p.m.