Triple
T12194395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anna Airy |
E290548
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Airy |
E753775
|
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: Airy | Statement: [Anna Airy, familyName, Airy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Airy Context triple: [Anna Airy, familyName, Airy]
-
A.
Airy
chosen
Airy is a surname most notably associated with George Biddell Airy, a prominent 19th-century English astronomer and Astronomer Royal.
-
B.
Ethereal
Ethereal was the original name of Wireshark, a widely used open-source network protocol analyzer for troubleshooting, analysis, and education.
-
C.
Breeze
Breeze is a web conferencing and e-learning software platform originally developed by Macromedia for online presentations, training, and collaboration.
-
D.
Breezy
Breezy is a 1973 romantic drama film directed by Clint Eastwood about a free-spirited young woman who forms an unlikely relationship with a middle-aged man.
-
E.
Lofty
Lofty is the nickname of Nat Lofthouse, the legendary English footballer famed for his prolific goal-scoring with Bolton Wanderers and England in the mid-20th century.
- 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_69d6ab64de5881908d56eb7a75c6cc69 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91c55a5a881909c0eea2d83c00f49 |
completed | April 10, 2026, 3:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60a8f31508190972d282b5a8816df |
completed | May 2, 2026, 2:30 p.m. |
Created at: April 8, 2026, 9:50 p.m.