Triple
T2623435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SED |
E59061
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | SED |
E59061
|
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: SED | Statement: [SED, shortName, SED]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SED Context triple: [SED, shortName, SED]
-
A.
SED
chosen
SED was the ruling Marxist–Leninist party that governed East Germany (the German Democratic Republic) from its founding in 1949 until the end of communist rule in 1989.
-
B.
SES
SES is the commonly used abbreviation for St Edward's School, a co-educational independent boarding and day school in Oxford, England.
-
C.
SEP
SEP is the Mexican federal government department responsible for overseeing and regulating the national education system.
-
D.
SEN
SEN is the three-letter IATA airport code for London Southend Airport in the United Kingdom.
-
E.
SE
SE is the official two-letter postal abbreviation for the Brazilian state of Sergipe.
- 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_69ab4ac558388190962492cd2e1b0ce6 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd8af06fc8190ab48d746b8c8892b |
completed | March 7, 2026, 7:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af909b7d9881908930a98d004998fb |
completed | March 10, 2026, 3:31 a.m. |
Created at: March 6, 2026, 9:50 p.m.