Triple
T17854626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Edward O'Hare |
E445898
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object | Edward |
E5488
|
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: Edward | Statement: [Edward O'Hare, hasGivenName, Edward]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Edward Context triple: [Edward O'Hare, hasGivenName, Edward]
-
A.
Edward
chosen
Edward is a masculine given name of English origin, historically associated with kings of England and notable figures such as U.S. Senator Edward M. Kennedy.
-
B.
Richard
Richard is a common masculine given name of Germanic origin, widely used in English-speaking countries.
-
C.
George
George is the given name of George W. McLaurin, the first African American student admitted to the University of Oklahoma.
-
D.
George
George is the given name of George M. Whitesides, a prominent American chemist known for his influential work in materials science, nanotechnology, and surface chemistry.
-
E.
George
George is the curious young protagonist of the children's science adventure book series "George's Secret Key to the Universe," co-authored by Stephen Hawking.
- 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_69d8b9f26f18819089c9e43250bee6ae |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4978af9b0819091780281344f5352 |
completed | April 19, 2026, 8:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0313ca5bac819089bedd1ee1b0546a |
completed | May 12, 2026, 11:49 a.m. |
Created at: April 10, 2026, 10:17 a.m.