Triple
T16983323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henry of Portugal |
E411998
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Henry |
E254557
|
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 of Portugal, givenName, Henry]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Henry Context triple: [Henry of Portugal, givenName, Henry]
-
A.
Henry
chosen
Henry is a masculine given name of Germanic origin that has been widely used by European royalty and notable historical figures.
-
B.
Henry
Henry is the given name of Henry Nottidge Moseley, a 19th-century English naturalist and professor known for his work in zoology and participation in the Challenger expedition.
-
C.
Henry
Henry is the vehicle registration code used on license plates to identify Henry County in the state of Indiana.
-
D.
Henry
Henry is the middle name of the famed American gambler, gunfighter, and dentist Doc Holliday.
-
E.
Henry
Henry is the middle name of George H. Thomas, a prominent Union general during the American Civil War.
- 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_69d886ca8f348190812768ea8d5055ce |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d188ede48190baead48aac84c78d |
completed | April 18, 2026, 6:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a011b412dd48190862fde6d1656113d |
completed | May 10, 2026, 11:56 p.m. |
Created at: April 10, 2026, 5:32 a.m.