Triple
T15639203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Karachi |
E376022
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | KU |
E376022
|
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: KU | Statement: [University of Karachi, abbreviation, KU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KU Context triple: [University of Karachi, abbreviation, KU]
-
A.
KU
KU is a common abbreviation for Kyoto University, a prestigious national research university in Kyoto, Japan.
-
B.
KU
chosen
KU is a common abbreviation for the University of Karachi, a major public research university in Karachi, Pakistan.
-
C.
KU
KU is the commonly used abbreviation for Kutztown University of Pennsylvania, a public university located in Kutztown, Pennsylvania.
-
D.
KU
KU is the commonly used abbreviation for the University of Kashmir, a major public university located in Srinagar, Jammu and Kashmir, India.
-
E.
KU
KU is the University of Kansas, a major public research university in Lawrence, Kansas, known for its strong athletics and distinctive school traditions.
- 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_69d85cd035a48190b73d5579ab73969a |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ed06b388190bfebb77fe70e7df1 |
completed | April 16, 2026, 2:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff5f4b693c81908fd324a5e92fc23c |
completed | May 9, 2026, 4:22 p.m. |
Created at: April 10, 2026, 4:14 a.m.