Triple
T721413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cybersecurity Information Sharing Act of 2015 |
E14623
|
entity |
| Predicate | yearOfPassage |
P18542
|
FINISHED |
| Object | 2015 |
—
|
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: 2015 | Statement: [Cybersecurity Information Sharing Act of 2015, yearOfPassage, 2015]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearOfPassage Context triple: [Cybersecurity Information Sharing Act of 2015, yearOfPassage, 2015]
-
A.
yearOfFilmAppearance
Indicates the specific year in which a film appearance by an entity took place.
-
B.
filmReleaseYear
Indicates the calendar year in which a film was first officially released to the public.
-
C.
discoveryYear
Indicates the calendar year in which something was first discovered or identified.
-
D.
compositionYear
Indicates the year in which a work (such as a piece of music, art, or literature) was originally created or composed.
-
E.
recordingYear
Indicates the specific calendar year in which something (such as audio, video, or data) was recorded.
- F. None of above. chosen
Provenance (4 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_69a4934c753c81909b309027e48b9b3a |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a58fa41c819082de2cc4e0cb2943 |
completed | March 1, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69a4a4f513608190b716b939d574c292 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a57267c481909790a1fda3fced08 |
completed | March 1, 2026, 8:45 p.m. |
Created at: March 1, 2026, 7:37 p.m.