Triple
T15439140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Graham Spanier |
E369851
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Graham Spanier |
E369851
|
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 Spanier | Statement: [Graham Spanier, name, Graham Spanier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Graham Spanier Context triple: [Graham Spanier, name, Graham Spanier]
-
A.
Graham Spanier
chosen
Graham Spanier is an American academic and former president of Pennsylvania State University whose tenure ended amid the Jerry Sandusky child abuse scandal.
-
B.
Doug Beattie
Doug Beattie is a Northern Irish politician and former British Army officer who serves as the leader of the Ulster Unionist Party (UUP).
-
C.
John Browne
John Browne is a British businessman and former CEO of BP who has written about leadership, corporate responsibility, and LGBT inclusion in the workplace.
-
D.
Gerry Hambling
Gerry Hambling was a British film editor known for his long collaboration with director Alan Parker on films such as "Bugsy Malone," "Midnight Express," and "Mississippi Burning."
-
E.
Graham Baldwin
Graham Baldwin is a British academic and university leader who serves as the vice-chancellor of the University of Central Lancashire.
- 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_69ff21a7d44481909a26b5cc331a3259 |
completed | May 9, 2026, 11:59 a.m. |
Created at: April 10, 2026, 3:21 a.m.