Triple
T11173451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liz Cooper |
E264342
|
entity |
| Predicate | radioSeriesFormat |
P9706
|
FINISHED |
| Object | situation comedy |
—
|
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: situation comedy | Statement: [Liz Cooper, radioSeriesFormat, situation comedy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: radioSeriesFormat Context triple: [Liz Cooper, radioSeriesFormat, situation comedy]
-
A.
hasRadioSeries
Indicates that one entity is associated with, or is the subject of, a radio series based on it or about it.
-
B.
radioFormat
chosen
Indicates the specific type or style of radio programming or broadcast format associated with an entity.
-
C.
narrativeSeries
Indicates that one narrative work belongs to, or is part of, an ordered series of related narratives.
-
D.
reporterSeries
Indicates that a reporter is associated with, contributes to, or is part of a particular series of reports or stories.
-
E.
typicalBroadcastFormat
Indicates the usual or standard broadcast format in which something (such as a program or content) is typically transmitted.
- 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_69d6aa9dafac8190bd90d2c74f661aa7 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e897774c819088ebc7231cebfba6 |
completed | April 9, 2026, 5:57 p.m. |
| PD | Predicate disambiguation | batch_69d75cf0e6e88190973694abe2990973 |
completed | April 9, 2026, 8:01 a.m. |
Created at: April 8, 2026, 9:29 p.m.