Triple
T5590745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Debbie Reynolds Show |
E146869
|
entity |
| Predicate | followedTrend |
P5318
|
FINISHED |
| Object | suburban family sitcoms of the 1960s |
—
|
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: suburban family sitcoms of the 1960s | Statement: [The Debbie Reynolds Show, followedTrend, suburban family sitcoms of the 1960s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: followedTrend Context triple: [The Debbie Reynolds Show, followedTrend, suburban family sitcoms of the 1960s]
-
A.
followedIn
Indicates that one entity began following or subscribing to another entity, typically in a social or sequential context.
-
B.
followedSign
Indicates that an entity proceeded in accordance with, or took action based on, a particular sign or posted instruction.
-
C.
hasTrend
chosen
Indicates that something exhibits or is associated with a particular pattern of change or direction over time.
-
D.
eraFollowed
Indicates that one historical era comes directly after another in chronological sequence.
-
E.
adoptedFollowing
Indicates that one entity formally took on or implemented another entity after or as a result of the occurrence of a preceding event, state, or action.
- 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_69c009036c408190981a8d690b679b67 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020a1d4cc8190a52264dfba6aa011 |
completed | March 22, 2026, 5:02 p.m. |
| PD | Predicate disambiguation | batch_69c01b16b9bc8190ab0b945507d90e05 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:38 p.m.