Triple
T470488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vrije Universiteit Amsterdam |
E8543
|
entity |
| Predicate | EUTimesRankingRange |
P1944
|
FINISHED |
| Object | top 100–200 in Europe |
—
|
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: top 100–200 in Europe | Statement: [Vrije Universiteit Amsterdam, EUTimesRankingRange, top 100–200 in Europe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: EUTimesRankingRange Context triple: [Vrije Universiteit Amsterdam, EUTimesRankingRange, top 100–200 in Europe]
-
A.
globalRanking
Indicates the position or status of an entity relative to all comparable entities worldwide according to some ranking criteria.
-
B.
GDPPerCapitaRanking
Indicates the relative position of an entity in an ordered list based on its gross domestic product (GDP) per person.
-
C.
populationRank
Indicates the relative position of an entity in an ordered list based on the size of its population.
-
D.
hasPopulationRank
Indicates the relative position of an entity in an ordered list based on the size of its population.
-
E.
rankedAs
chosen
Indicates that one entity is assigned a specific position or level in an ordered ranking relative to others.
- 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_69a2e7f3aeb48190a19453e3a043f486 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2efef8b788190857ebf66df562d59 |
completed | Feb. 28, 2026, 1:38 p.m. |
| PD | Predicate disambiguation | batch_69a2edecefb081908331ef8b9edf6636 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.