Triple
T15586964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FDFA |
E374646
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
EDA (German)
EDA (German) is the German abbreviation for the Swiss Federal Department of Foreign Affairs, the government ministry responsible for Switzerland’s foreign policy and international relations.
|
E1165785
|
NE FINISHED |
How this triple was built (4 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 (German) | Statement: [FDFA, abbreviation, EDA (German)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: EDA (German) Context triple: [FDFA, abbreviation, EDA (German)]
-
A.
Deutch
Deutch is a surname most notably associated with John M. Deutch, an American chemist, academic, and former Director of Central Intelligence.
-
B.
DEU
DEU is the three-letter ISO 3166-1 alpha-3 country code representing Germany.
-
C.
Aa (German)
Aa (German) is the German name for several small rivers in Central Europe, most notably tributaries in Germany and Switzerland.
-
D.
GRMN
GRMN is a high-performance sub-brand of Toyota’s Gazoo Racing division, offering limited-run, track-focused versions of select Toyota models.
-
E.
German ICE
The German ICE (InterCity Express) is Germany’s high-speed train system, known for its fast, comfortable long-distance rail service and advanced engineering.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: EDA (German) Triple: [FDFA, abbreviation, EDA (German)]
Generated description
EDA (German) is the German abbreviation for the Swiss Federal Department of Foreign Affairs, the government ministry responsible for Switzerland’s foreign policy and international relations.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: EDA (German) Target entity description: EDA (German) is the German abbreviation for the Swiss Federal Department of Foreign Affairs, the government ministry responsible for Switzerland’s foreign policy and international relations.
-
A.
Deutch
Deutch is a surname most notably associated with John M. Deutch, an American chemist, academic, and former Director of Central Intelligence.
-
B.
DEU
DEU is the three-letter ISO 3166-1 alpha-3 country code representing Germany.
-
C.
Aa (German)
Aa (German) is the German name for several small rivers in Central Europe, most notably tributaries in Germany and Switzerland.
-
D.
GRMN
GRMN is a high-performance sub-brand of Toyota’s Gazoo Racing division, offering limited-run, track-focused versions of select Toyota models.
-
E.
German ICE
The German ICE (InterCity Express) is Germany’s high-speed train system, known for its fast, comfortable long-distance rail service and advanced engineering.
- F. None of above. chosen
Provenance (5 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. |
| NEDg | Description generation | batch_69ff50183f608190811cbff769cdd110 |
completed | May 9, 2026, 3:17 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff52eedbc08190be2f62326b00c8c7 |
completed | May 9, 2026, 3:29 p.m. |
Created at: April 10, 2026, 4:11 a.m.