Triple
T18519889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Public Law 107-347 (Title V) |
E452556
|
entity |
| Predicate | hasAcronym |
P43
|
FINISHED |
| Object | CIPSEA |
—
|
NE NERFINISHED |
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: CIPSEA | Statement: [Public Law 107-347 (Title V), hasAcronym, CIPSEA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CIPSEA Context triple: [Public Law 107-347 (Title V), hasAcronym, CIPSEA]
-
A.
CIPSEA
chosen
CIPSEA is a U.S. federal law that governs the confidential treatment of data collected for statistical purposes and promotes efficient data sharing among statistical agencies.
-
B.
CESA
CESA is a California state law that protects plant and animal species at risk of extinction by regulating activities that may harm them or their habitats.
-
C.
SEAS
SEAS is the acronym for Yale University's School of Engineering & Applied Science, which houses its engineering and applied science programs.
-
D.
SEAS
SEAS is the abbreviation for the Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University's engineering and applied sciences school.
-
E.
SEAS
SEAS is the University of Pennsylvania’s engineering and applied science school, offering undergraduate and graduate programs in fields such as computer science, bioengineering, and mechanical engineering.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d386df84819092355ebb260d848e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5338ce7e481908ee69ffe4f30d5a4 |
completed | April 19, 2026, 7:57 p.m. |
Created at: April 10, 2026, 11:37 a.m.