Triple
T15774059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Verband der Eisenbahner Deutschlands |
E382440
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object |
VED
VED is the abbreviation for the Verband der Eisenbahner Deutschlands, a German association representing the interests of railway workers.
|
E1175619
|
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: VED | Statement: [Verband der Eisenbahner Deutschlands, hasAbbreviation, VED]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: VED Context triple: [Verband der Eisenbahner Deutschlands, hasAbbreviation, VED]
-
A.
VEN
VEN is the three-letter ISO 3166-1 alpha-3 country code assigned to Venezuela for international identification and data standards.
-
B.
VE
VE is the Italian vehicle registration code assigned to the Metropolitan City of Venice.
-
C.
VE
VE is the two-letter ISO 3166-1 alpha-2 country code assigned to Venezuela for international standardization and identification purposes.
-
D.
VES
VES is an abbreviation for the Virtual Execution System, a runtime environment designed to execute managed code in a platform-independent manner.
-
E.
VER
VER is the IATA airport code for General Heriberto Jara International Airport serving the city of Veracruz, Mexico.
- 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: VED Triple: [Verband der Eisenbahner Deutschlands, hasAbbreviation, VED]
Generated description
VED is the abbreviation for the Verband der Eisenbahner Deutschlands, a German association representing the interests of railway workers.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: VED Target entity description: VED is the abbreviation for the Verband der Eisenbahner Deutschlands, a German association representing the interests of railway workers.
-
A.
VEN
VEN is the three-letter ISO 3166-1 alpha-3 country code assigned to Venezuela for international identification and data standards.
-
B.
VE
VE is the Italian vehicle registration code assigned to the Metropolitan City of Venice.
-
C.
VE
VE is the two-letter ISO 3166-1 alpha-2 country code assigned to Venezuela for international standardization and identification purposes.
-
D.
VES
VES is an abbreviation for the Virtual Execution System, a runtime environment designed to execute managed code in a platform-independent manner.
-
E.
VER
VER is the IATA airport code for General Heriberto Jara International Airport serving the city of Veracruz, Mexico.
- 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_69d86da09a10819082fe9797b23e4664 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e05198c1588190a65e23c18443eb5c |
completed | April 16, 2026, 3:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff877e67b881908a67b9acc79d998f |
completed | May 9, 2026, 7:14 p.m. |
| NEDg | Description generation | batch_69ff88358e408190a8d7424fc495d4fa |
completed | May 9, 2026, 7:17 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff88f192a08190acbc2c3fc98c65c8 |
completed | May 9, 2026, 7:20 p.m. |
Created at: April 10, 2026, 4:47 a.m.