Triple
T7461393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Public Law 110-343 |
E176256
|
entity |
| Predicate | acronym |
P43
|
FINISHED |
| Object | EESA |
E666583
|
NE 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: EESA | Statement: [Public Law 110-343, acronym, EESA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: EESA Context triple: [Public Law 110-343, acronym, EESA]
-
A.
EESA
chosen
EESA is a 2008 U.S. federal law that authorized the Treasury to address the financial crisis by purchasing troubled assets and stabilizing the banking system.
-
B.
EAPS
EAPS is an academic department focused on the study and research of Earth, its atmosphere, and other planetary bodies.
-
C.
ECASA
ECASA is a Cuban state-owned company responsible for managing and operating the country’s civil airports and air terminals.
-
D.
ECO Science Foundation
The ECO Science Foundation is a specialized regional body that promotes scientific research, cooperation, and capacity-building among the member states of the Economic Cooperation Organization.
-
E.
ESE
ESE is a highly competitive Indian national-level examination conducted by the Union Public Service Commission to recruit engineers for prestigious technical and managerial positions in various government departments and public sector organizations.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c69f21632481908bf83f6c6da897e3 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f3d6cf8c8190a31cac121d151d78 |
completed | March 27, 2026, 9:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c83c5bab90819093431470e0e8c0e3 |
completed | March 28, 2026, 8:38 p.m. |
Created at: March 27, 2026, 3:38 p.m.