Triple
T1512196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George W. Norris |
E32037
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Norris
Norris is a surname most notably associated with influential American politician George W. Norris, a progressive-era U.S. senator from Nebraska.
|
E172464
|
NE FINISHED |
How this triple was built (4 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: [George W. Norris, familyName, Norris]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Norris Context triple: [George W. Norris, familyName, Norris]
-
A.
Snodgrass
Snodgrass is a surname of English and Scottish origin borne by various notable individuals in sports, politics, and the arts.
-
B.
Hayes
Hayes is a suburban district in southeast London, England, known for its residential character and green spaces within the London Borough of Bromley.
-
C.
Farguson
Farguson is an alternative spelling of the surname Ferguson, which is of Scottish origin.
-
D.
Milhous
Milhous is the distinctive middle name of Richard Nixon, the 37th president of the United States.
-
E.
Eldridge
Eldridge is an English-language surname of Old English origin, borne by various notable individuals across fields such as politics, the arts, and sports.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Norris Triple: [George W. Norris, familyName, Norris]
Generated description
Norris is a surname most notably associated with influential American politician George W. Norris, a progressive-era U.S. senator from Nebraska.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Norris Target entity description: Norris is a surname most notably associated with influential American politician George W. Norris, a progressive-era U.S. senator from Nebraska.
-
A.
Snodgrass
Snodgrass is a surname of English and Scottish origin borne by various notable individuals in sports, politics, and the arts.
-
B.
Hayes
Hayes is a suburban district in southeast London, England, known for its residential character and green spaces within the London Borough of Bromley.
-
C.
Farguson
Farguson is an alternative spelling of the surname Ferguson, which is of Scottish origin.
-
D.
Milhous
Milhous is the distinctive middle name of Richard Nixon, the 37th president of the United States.
-
E.
Eldridge
Eldridge is an English-language surname of Old English origin, borne by various notable individuals across fields such as politics, the arts, and sports.
- F. None of above. chosen
Provenance (5 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_69a885e8caf88190a5fbb6159ce87786 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa61db41c88190a2d97cc9cbbc3f06 |
completed | March 6, 2026, 5:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad233e6e748190929b3f339cc9bd4b |
completed | March 8, 2026, 7:20 a.m. |
| NEDg | Description generation | batch_69ad23e279e88190ae341af34ea98487 |
completed | March 8, 2026, 7:23 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad24f7d8b081909241ab3995172f4d |
completed | March 8, 2026, 7:27 a.m. |
Created at: March 4, 2026, 7:26 p.m.