Triple
T1450999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Gothenburg |
E31289
|
entity |
| Predicate | cityRankInSwedenBySize |
P28749
|
FINISHED |
| Object | second-largest city university in Sweden |
—
|
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: second-largest city university in Sweden | Statement: [University of Gothenburg, cityRankInSwedenBySize, second-largest city university in Sweden]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityRankInSwedenBySize Context triple: [University of Gothenburg, cityRankInSwedenBySize, second-largest city university in Sweden]
-
A.
areaRank
Indicates the relative ordering or position of an entity based on the size of its area compared to others.
-
B.
citySigned
Indicates that a city has formally signed or endorsed an agreement, document, or commitment.
-
C.
haveAutonomousRegionWithSwedishMajority
Indicates that an entity possesses an autonomous region in which the majority of the population is Swedish.
-
D.
cityArea
Indicates the total geographic area covered by a city.
-
E.
areaRankingInEstonia
Indicates the relative position of something in a size-based ranking specifically within the context of Estonia.
- 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_69a499171a28819085b993a3ac78e363 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c57bc0908190a57e6bc3d20d5e3c |
completed | March 1, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69a4c47cdbd0819092022344a2f4ad7b |
completed | March 1, 2026, 10:58 p.m. |
| PDg | Predicate description generation | batch_69a4c55508948190922aee3230a4323e |
completed | March 1, 2026, 11:01 p.m. |
Created at: March 1, 2026, 8 p.m.