Triple
T8070236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KFAT |
E188351
|
entity |
| Predicate | FAAIdentifier |
P420
|
FINISHED |
| Object | FAT |
E188350
|
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: FAT | Statement: [KFAT, FAAIdentifier, FAT]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FAT Context triple: [KFAT, FAAIdentifier, FAT]
-
A.
FAT
FAT is the commonly used abbreviation for the FA Trophy, an English football knockout competition for non-league clubs.
-
B.
FAT
chosen
FAT is the three-letter IATA airport code for Fresno Yosemite International Airport in Fresno, California.
-
C.
FAT
FAT (File Allocation Table) is an older, simple file system commonly used on removable storage devices and supported by many operating systems, but lacking advanced features like built-in encryption and journaling.
-
D.
FAD
FAD is the Faculty of Arts and Design at the University of Canberra, offering creative and humanities-focused education and research programs.
-
E.
FAD
FAD is the ICAO airline designator assigned to flyadeal, a Saudi Arabian low-cost carrier based in Jeddah.
- 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_69ca82b42674819086840efea12478e5 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3ffe29188190834ec4f71043a99d |
completed | March 31, 2026, 3:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ccbe67d9dc8190ad72e3f5ce7478e3 |
completed | April 1, 2026, 6:42 a.m. |
Created at: March 30, 2026, 5:27 p.m.