Triple
T15671235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ruud Lubbers |
E377315
|
entity |
| Predicate | termLengthAsPrimeMinisterInYears |
P119691
|
FINISHED |
| Object | 11.75 |
—
|
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: 11.75 | Statement: [Ruud Lubbers, termLengthAsPrimeMinisterInYears, 11.75]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: termLengthAsPrimeMinisterInYears Context triple: [Ruud Lubbers, termLengthAsPrimeMinisterInYears, 11.75]
-
A.
primeMinisterTerm
Indicates the period of time during which a person holds the office and exercises the role of prime minister of a government.
-
B.
numberOfTermsAsPrimeMinister
Indicates how many separate terms an individual has served in the role of prime minister.
-
C.
numberOfTermInOffice
Indicates the specific ordinal count of how many terms an entity has served in a particular office or position.
-
D.
endTimeFirstTermAsPrimeMinister
Indicates the date and time when an individual’s first term serving as prime minister comes to an end.
-
E.
ageAtFirstBecomingPrimeMinister
Indicates the age a person was when they first assumed the office of prime minister.
- F. None of above. chosen
Provenance (4 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_69d85cd2e28481909d4e975bee20872f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04f13b1b08190beabc9f4098aa096 |
completed | April 16, 2026, 2:53 a.m. |
| PD | Predicate disambiguation | batch_69deda8b36a4819081cb5708fe77ef51 |
completed | April 15, 2026, 12:23 a.m. |
| PDg | Predicate description generation | batch_69dff7f3016c8190ac68d76e65e07af4 |
completed | April 15, 2026, 8:41 p.m. |
Created at: April 10, 2026, 4:16 a.m.