Triple
T18761104
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TV Buddha |
E458769
|
entity |
| Predicate | firstPresentedInPeriod |
P33287
|
FINISHED |
| Object | 1970s |
—
|
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: 1970s | Statement: [TV Buddha, firstPresentedInPeriod, 1970s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstPresentedInPeriod Context triple: [TV Buddha, firstPresentedInPeriod, 1970s]
-
A.
firstPresentedFor
Indicates that one entity was initially introduced, submitted, or shown to another entity at a particular time or context.
-
B.
firstAppearedAt
Indicates the point in time or specific event at which an entity was first introduced, observed, or became known.
-
C.
firstAppeared
Indicates the earliest known time or context in which an entity was introduced, observed, or came into existence.
-
D.
appearedThroughPeriod
Indicates that an entity was present or manifested continuously or recurrently throughout a specified time period.
-
E.
firstPresentedDecade
chosen
Indicates the decade during which something was first presented or introduced.
- 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_69d8d395dba0819087568404508590cb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e58d7ecca881909d6c262837b621b3 |
completed | April 20, 2026, 2:20 a.m. |
| PD | Predicate disambiguation | batch_69e48d0b7b708190877951b6e6cdcbc4 |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:52 a.m.