Triple
T24600051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Council Regulation (EC) No 1698/2005 |
E608797
|
entity |
| Predicate | numberInYear |
P12446
|
FINISHED |
| Object | 1698/2005 |
—
|
LITERAL 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: 1698/2005 | Statement: [Council Regulation (EC) No 1698/2005, numberInYear, 1698/2005]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberInYear Context triple: [Council Regulation (EC) No 1698/2005, numberInYear, 1698/2005]
-
A.
hasNumberInYear
chosen
Indicates that a specific number is associated with or occurs within a given year.
-
B.
yearType
Indicates the classification or category assigned to a specific year (e.g., academic, fiscal, calendar, leap).
-
C.
yearPassed
Indicates that a specified number of calendar years has elapsed between two time points or events.
-
D.
yearObserved
Indicates the specific calendar year during which the referenced event, condition, or measurement was observed or recorded.
-
E.
countsYearsFrom
Indicates a temporal relationship where the number of years is measured starting from a specified reference point or event.
- F. None of above.
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_69e2c4cf54248190af7b0c2d9ade9830 |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6ca751c8190a040c10d701ecf3a |
completed | April 30, 2026, 12:48 a.m. |
Created at: April 18, 2026, 2:30 a.m.