Triple
T24168016
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Whistling Death |
E599047
|
entity |
| Predicate | hasCauseOfSound |
P155570
|
FINISHED |
| Object | airflow over wing-root air intakes and gaps |
—
|
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: airflow over wing-root air intakes and gaps | Statement: [Whistling Death, hasCauseOfSound, airflow over wing-root air intakes and gaps]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCauseOfSound Context triple: [Whistling Death, hasCauseOfSound, airflow over wing-root air intakes and gaps]
-
A.
hasSound
Indicates that an entity produces, emits, or is associated with a particular sound.
-
B.
usesSound
Indicates that one entity employs or relies on sound as a means or tool in relation to another entity or context.
-
C.
containsSound
Indicates that one entity includes, embodies, or produces the sound associated with another entity.
-
D.
hasCatchySound
Indicates that something possesses an appealing, memorable, or attractive auditory quality.
-
E.
hasHeavierSoundThan
Indicates that one entity produces or is associated with a sound that is sonically heavier, more intense, or more forceful than that of another entity.
- 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_69e288cbd62881909de32ca64a70c17b |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f27c9ddfcc819096697a844b300cce |
completed | April 29, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69f1c42f942c8190b103ff29a60fef34 |
completed | April 29, 2026, 8:41 a.m. |
| PDg | Predicate description generation | batch_69f27a753ca8819095706970d368f762 |
completed | April 29, 2026, 9:39 p.m. |
Created at: April 17, 2026, 11:33 p.m.