Triple
T749047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Halsey Jr. |
E15405
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | William |
E772
|
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: William | Statement: [William Halsey Jr., givenName, William]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: William Context triple: [William Halsey Jr., givenName, William]
-
A.
William
chosen
William is a common masculine given name of Germanic origin, widely used in English-speaking countries.
-
B.
Thomas
Thomas is the given name of Thomas Cranmer, the 16th-century Archbishop of Canterbury and a leading figure in the English Reformation.
-
C.
Thomas
Thomas is a common masculine given name of Aramaic origin, widely used in English-speaking and many other cultures.
-
D.
Thomas
Thomas is the given name of Confederate General "Stonewall" Jackson, a prominent military leader during the American Civil War.
-
E.
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.
- 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_69a493599a0081908da65f3407af1ef2 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a62f31888190b80cb0a7220f8d80 |
completed | March 1, 2026, 8:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a76d69ade481909322f5f28f0050e4 |
completed | March 3, 2026, 11:23 p.m. |
Created at: March 1, 2026, 7:37 p.m.