Triple
T5846252
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Isaac E. Avery |
E129718
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Avery |
E326811
|
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: Avery | Statement: [Isaac E. Avery, familyName, Avery]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Avery Context triple: [Isaac E. Avery, familyName, Avery]
-
A.
Avery
chosen
Avery is a publishing imprint known for releasing popular nonfiction books on topics such as health, psychology, and personal growth.
-
B.
Avery
Avery is the middle name of famed Canadian World War I flying ace Billy Bishop.
-
C.
Arons
Arons is the surname of Arnold B. Arons, a prominent American physicist and influential physics education researcher.
-
D.
Fay
Fay is a given name most famously associated with Canadian-American actress Fay Wray, the iconic star of the 1933 film "King Kong."
-
E.
Macy
Macy is a surname most prominently associated with R. H. Macy, the founder of the American department store chain Macy’s.
- 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_69c0084bd31c8190a796bb6284845e83 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0351157508190a78d2a7141e0cee8 |
completed | March 22, 2026, 6:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0a1a9ffa881908b38eeddb411c4ab |
completed | March 23, 2026, 2:12 a.m. |
Created at: March 22, 2026, 3:55 p.m.