Triple
T21682025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ferdowsi University of Mashhad |
E535131
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | FUM |
—
|
NE NERFINISHED |
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: FUM | Statement: [Ferdowsi University of Mashhad, abbreviation, FUM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FUM Context triple: [Ferdowsi University of Mashhad, abbreviation, FUM]
-
A.
FUM
chosen
FUM is an abbreviation for Ferdowsi University of Mashhad, a major public research university in Mashhad, Iran.
-
B.
FUM
FUM is the station code for Fulham Broadway, a London Underground station on the District line in the Fulham area of southwest London.
-
C.
FUMA
FUMA is the art museum of Flinders University in South Australia, known for its diverse collections of Australian, Aboriginal, and international art.
-
D.
FUK
FUK is the IATA airport code for Fukuoka Airport, a major international and domestic air hub serving the city of Fukuoka in Japan.
-
E.
Fu
Fu is a Chinese surname borne by various notable historical and contemporary figures across politics, arts, and other fields.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c469b6ec8190aee4cadd1527db91 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef96c69990819088a1134ecea09099 |
completed | April 27, 2026, 5:03 p.m. |
Created at: April 16, 2026, 6:43 p.m.