Triple
T15439218
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Graham Gooch |
E369853
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Graham |
E75501
|
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: Graham | Statement: [Graham Gooch, givenName, Graham]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Graham Context triple: [Graham Gooch, givenName, Graham]
-
A.
Graham
Graham is the surname of Elizabeth Arden, the pioneering Canadian-American businesswoman who founded the iconic Elizabeth Arden cosmetics empire.
-
B.
Graham
chosen
Graham is a masculine given name of English origin, historically derived from a surname and commonly used in English-speaking countries.
-
C.
Grahame
Grahame is a surname of English and Scottish origin borne by various notable individuals.
-
D.
Gordon
Gordon is the middle name of the famed Romantic poet Lord Byron, whose full name is George Gordon Byron.
-
E.
Gordon
Gordon is a masculine given name of English origin, often associated with notable figures in politics, entertainment, and sports.
- 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_69d85a19180081909925012fbf4e62a3 |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03eddf258819082679970b7d2b6af |
completed | April 16, 2026, 1:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff4c3293dc819097f9e56963c333ee |
completed | May 9, 2026, 3:01 p.m. |
Created at: April 10, 2026, 3:21 a.m.