Triple
T512635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lancaster University |
E10638
|
entity |
| Predicate | THEWorldRankingRange |
P733
|
FINISHED |
| Object | top 150–200 globally in many years |
—
|
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 150–200 globally in many years | Statement: [Lancaster University, THEWorldRankingRange, top 150–200 globally in many years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: THEWorldRankingRange Context triple: [Lancaster University, THEWorldRankingRange, top 150–200 globally in many years]
-
A.
globalRanking
chosen
Indicates the position or status of an entity relative to all comparable entities worldwide according to some ranking criteria.
-
B.
populationRank
Indicates the relative position of an entity in an ordered list based on the size of its population.
-
C.
fifaRankingHighest
Indicates that the subject has the highest FIFA ranking among a specified group or within a given context.
-
D.
fifaLikeRankingType
Indicates a ranking system or classification that follows the style, rules, or methodology of FIFA’s official rankings.
-
E.
rankedAs
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_69a2e84a0d08819087e01863fcd9abf1 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f232fa688190b08a2fe3f22c7a6e |
completed | Feb. 28, 2026, 1:48 p.m. |
| PD | Predicate disambiguation | batch_69a2f013c05481909e6dc87e7b20ebd8 |
completed | Feb. 28, 2026, 1:39 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.