Triple
T240941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clean Air Act |
E4929
|
entity |
| Predicate | includesTitle |
P3254
|
FINISHED |
| Object | Title I – Air Pollution Prevention and Control |
—
|
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: Title I – Air Pollution Prevention and Control | Statement: [Clean Air Act, includesTitle, Title I – Air Pollution Prevention and Control]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesTitle Context triple: [Clean Air Act, includesTitle, Title I – Air Pollution Prevention and Control]
-
A.
containsTitle
chosen
Indicates that one entity includes or holds another entity’s title as part of its content or metadata.
-
B.
associatedTitle
Indicates that one entity has a title, designation, or formal label that is linked or relevant to another entity.
-
C.
title
Indicates that one entity serves as the formal name or designation of another entity.
-
D.
titleInEnglish
Indicates that an entity’s title or name is given in the English language.
-
E.
titleAlludesTo
Indicates that one title makes an indirect or suggestive reference to the content, theme, or another work associated with the other.
- 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_69a257c3d0708190b0871c4269d273e6 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25d35aa288190966b6e15af1525cb |
completed | Feb. 28, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69a25b60ad308190b12f119960a8bde7 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.