Triple
T15586961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FDFA |
E374646
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | EDA |
unclear NED1
|
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: EDA | Statement: [FDFA, abbreviation, EDA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: EDA Context triple: [FDFA, abbreviation, EDA]
-
A.
EDA
EDA is a U.S. federal agency within the Department of Commerce that provides grants and technical assistance to support economic growth and job creation in distressed communities.
-
B.
EDA
EDA is the German-language abbreviation for Switzerland’s Federal Department of Foreign Affairs, which manages the country’s diplomatic relations and foreign policy.
-
C.
EDA
EDA is an agency of the European Union that supports and coordinates member states in developing defense capabilities and fostering military cooperation.
-
D.
EDA
EDA is a statistical approach to analyzing datasets through visualizations and summary statistics to uncover patterns, spot anomalies, and test assumptions before formal modeling.
-
E.
EECE
EECE is the commonly used abbreviation for the Department of Energy, Environmental & Chemical Engineering, an academic unit focused on research and education in sustainable energy, environmental protection, and chemical processes.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69d85ccd575081908909b71a3f3e3a61 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e4900408190aadb48b001db4169 |
completed | April 16, 2026, 2:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff4c5166d88190ab14c7779e3e8e1f |
completed | May 9, 2026, 3:01 p.m. |
Created at: April 10, 2026, 4:11 a.m.