Triple
T110280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henry Bessemer |
E2233
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Henry |
E9957
|
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: Henry | Statement: [Henry Bessemer, givenName, Henry]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Henry Context triple: [Henry Bessemer, givenName, Henry]
-
A.
Henry
chosen
Henry is the given name of Henry A. Kissinger, the influential American diplomat and political scientist who served as U.S. Secretary of State and National Security Advisor.
-
B.
George
George is the first name of George Washington, the first President of the United States and a key leader in the American Revolutionary War.
-
C.
Thomas
Thomas is the given name of Thomas Malthus, the influential English economist and demographer known for his theories on population growth and resource limits.
-
D.
Thomas
Thomas is the full given name of Tom Brady, the legendary NFL quarterback widely regarded as one of the greatest players in American football history.
-
E.
Robert
Robert is a common masculine given name of Germanic origin, widely used in English-speaking countries.
- 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_69a24fcdaeb48190a2d796677e4b3281 |
completed | Feb. 28, 2026, 2:15 a.m. |
| NER | Named-entity recognition | batch_69a256ce54b48190a3337f5f45d82859 |
completed | Feb. 28, 2026, 2:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a376555f5081909f8a6593aa5858c4 |
completed | Feb. 28, 2026, 11:12 p.m. |
Created at: Feb. 28, 2026, 2:20 a.m.