Triple
T8927258
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benaroya Hall |
E212565
|
entity |
| Predicate | soundIsolationFrom |
P61641
|
FINISHED |
| Object | nearby traffic and light rail vibrations |
—
|
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: nearby traffic and light rail vibrations | Statement: [Benaroya Hall, soundIsolationFrom, nearby traffic and light rail vibrations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: soundIsolationFrom Context triple: [Benaroya Hall, soundIsolationFrom, nearby traffic and light rail vibrations]
-
A.
soundInsulation
chosen
Indicates the degree to which one entity reduces or blocks the transmission of sound from another entity or environment.
-
B.
soundHeardDistanceApproximate
Indicates that a sound was heard at an estimated, not precisely measured, distance from the listener or reference point.
-
C.
soundCategory
Indicates the classification relationship where a sound is assigned to a particular category or type of sound.
-
D.
soundAmplification
Indicates that one entity increases the loudness or intensity of another entity’s sound.
-
E.
usesAudioFrom
Indicates that one entity incorporates or relies on the audio content produced or provided by another entity.
- 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_69ca839481d48190b42b037e0d0f636c |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6671557c81909f3837ffd6a15ffe |
completed | April 1, 2026, 12:27 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed3286c8190a21de2ee11f2639f |
completed | March 31, 2026, 11:54 p.m. |
Created at: March 30, 2026, 6:57 p.m.