Triple
T5689528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal District (Brazil) |
E125393
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object | DF |
E181037
|
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: DF | Statement: [Federal District (Brazil), vehicleRegistrationCode, DF]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DF Context triple: [Federal District (Brazil), vehicleRegistrationCode, DF]
-
A.
DF
chosen
DF is the vehicle registration code for Brazil’s Federal District, which includes the national capital, Brasília.
-
B.
GF
GF is the vehicle registration code assigned to the district that includes the Austrian town of Deutsch-Wagram.
-
C.
GF
GF is the two-letter ISO 3166-1 alpha-2 country code assigned to French Guiana.
-
D.
DFG
DFG is Germany’s central self-governing research funding organization, supporting scientific and academic research across all disciplines.
-
E.
DFG
DFG is the Massachusetts state agency responsible for conserving and managing fish, wildlife, and related natural resources.
- 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_69c0082bb19c8190823a4facd3cba79b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c023e1c6148190aeae7620bd9ee9d4 |
completed | March 22, 2026, 5:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c05a47457c8190bc75f11a7f011a8a |
completed | March 22, 2026, 9:08 p.m. |
Created at: March 22, 2026, 3:44 p.m.