Triple
T1954991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaley Cuoco |
E42244
|
entity |
| Predicate | activeInIndustryFrom |
P21215
|
FINISHED |
| Object | 1990s |
—
|
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: 1990s | Statement: [Kaley Cuoco, activeInIndustryFrom, 1990s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: activeInIndustryFrom Context triple: [Kaley Cuoco, activeInIndustryFrom, 1990s]
-
A.
historicallyActiveIn
Indicates that an entity was active or engaged in significant activities within a particular place or context during a past historical period.
-
B.
activeFrom
Indicates the starting point in time from which an entity or relationship is considered active or in effect.
-
C.
occupationBegan
Indicates the point in time when an entity started holding a particular occupation or job.
-
D.
activeInYear
Indicates that an entity was active, functioning, or operational during a specified year.
-
E.
activeInFieldFrom
chosen
Indicates that an entity is professionally or actively engaged in a particular field starting from a specified point in time.
- 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_69a8870eea088190a38781990812a9bc |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb353aa8c81909810347f9981a02f |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abaff3eda88190b643994cb4dfb8df |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:36 p.m.