Triple
T1687120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samuel Arnold |
E36467
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Arnold |
E22137
|
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: Arnold | Statement: [Samuel Arnold, familyName, Arnold]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arnold Context triple: [Samuel Arnold, familyName, Arnold]
-
A.
Arnold
chosen
Arnold is a common English and German surname borne by numerous notable individuals across fields such as science, politics, sports, and the arts.
-
B.
Arnold
Arnold is a market town and suburb in the county of Nottinghamshire, England, situated to the northeast of Nottingham.
-
C.
Alan
Alan is a masculine given name of Celtic origin that has been widely used in English-speaking countries.
-
D.
Kenneth
Kenneth is the formal given name of American country music singer, songwriter, and actor Kenny Rogers.
-
E.
Arnold Vinnius
Arnold Vinnius was a prominent 17th-century Dutch jurist and legal scholar whose influential commentaries helped shape the development and teaching of Roman-Dutch law.
- 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_69a886151508819084fa7f1ce6e05577 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa6293c368819094ab0f615e418647 |
completed | March 6, 2026, 5:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad71c344fc8190926db828cf09550e |
completed | March 8, 2026, 12:55 p.m. |
Created at: March 4, 2026, 7:29 p.m.