Triple
T6138531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Norris Dickinson |
E136897
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Norris |
E172464
|
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: Norris | Statement: [Mary Norris Dickinson, familyName, Norris]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Norris Context triple: [Mary Norris Dickinson, familyName, Norris]
-
A.
Norris
chosen
Norris is a surname most notably associated with influential American politician George W. Norris, a progressive-era U.S. senator from Nebraska.
-
B.
Norval
Norval is a small historic village in Ontario, Canada, known for its scenic Credit River setting and association with author Lucy Maud Montgomery.
-
C.
Morrisen
Morrisen is an alternative spelling or variant form of the surname Morrison.
-
D.
Snodgrass
Snodgrass is a surname of English and Scottish origin borne by various notable individuals in sports, politics, and the arts.
-
E.
Shadbolt
Shadbolt is a surname most notably associated with Sir Nigel Shadbolt, a prominent British computer scientist and artificial intelligence researcher.
- 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_69c008a179388190a3b5a081bbf46d55 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05c855a2481909801de9fd55686a4 |
completed | March 22, 2026, 9:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c135e78950819085a2fdd7538af4cb |
completed | March 23, 2026, 12:45 p.m. |
Created at: March 22, 2026, 4:15 p.m.