Triple
T15073963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stockholm University |
E379950
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | SU |
E379950
|
NE 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: SU | Statement: [Stockholm University, abbreviation, SU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SU Context triple: [Stockholm University, abbreviation, SU]
-
A.
SU
SU is the IATA airline designator for Aeroflot, Russia’s flag carrier and largest airline.
-
B.
SU
SU is the station code used to identify Summerhill railway station.
-
C.
SU
chosen
SU is the commonly used abbreviation for Stockholm University, a major public research university in Stockholm, Sweden.
-
D.
SU
SU is the commonly used abbreviation for Saurashtra University, a public higher education institution located in Gujarat, India.
-
E.
SU
SU is the common abbreviation for the Southern University Jaguars and Lady Jaguars athletic programs representing Southern University in collegiate sports.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d85cd7683881908d405c1b5d7b4f7f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69dff7fa0570819088a97b28173154cd |
completed | April 15, 2026, 8:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fea5cff69c8190b6252509c1aa7ebb |
completed | May 9, 2026, 3:11 a.m. |
Created at: April 10, 2026, 3:02 a.m.