Triple
T19664469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | At San Quentin |
E472164
|
entity |
| Predicate | hasLiveSpokenInterludes |
P108014
|
FINISHED |
| Object | banter with inmates |
—
|
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: banter with inmates | Statement: [At San Quentin, hasLiveSpokenInterludes, banter with inmates]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLiveSpokenInterludes Context triple: [At San Quentin, hasLiveSpokenInterludes, banter with inmates]
-
A.
hasLiveSpokenIntroductions
Indicates that one entity provides live, spoken introductory remarks or presentations for another entity or event.
-
B.
containsInterludes
Indicates that one entity (typically a work or composition) includes one or more interludes within its structure.
-
C.
isSpokenAlong
Indicates that something (typically a language or dialect) is used or spoken in the regions or areas that follow a particular path, boundary, or route.
-
D.
hasSpokenWordSections
chosen
Indicates that something contains or includes sections where words are spoken rather than sung or played.
-
E.
hasSpokenWordIntro
Indicates that an entity includes or features an introductory segment performed in spoken word form.
- 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_69d8e514f2e08190ba70a4449519d218 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6416749d48190b141a6acd20c9694 |
completed | April 20, 2026, 3:08 p.m. |
| PD | Predicate disambiguation | batch_69e514e941008190898d978d7bde91e4 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:45 p.m.