Triple
T5649760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgina Chapman |
E124473
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Chapman |
E72439
|
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: Chapman | Statement: [Georgina Chapman, familyName, Chapman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chapman Context triple: [Georgina Chapman, familyName, Chapman]
-
A.
Chapman
chosen
Chapman is a surname most famously associated with Graham Chapman, a British comedian, writer, and member of the Monty Python comedy group.
-
B.
Champ
Champ is a supporting character in the action-spy film "Kingsman: The Golden Circle," serving as a high-ranking member of the American Statesman organization.
-
C.
Champ
Champ is the Dallas Mavericks’ horse-themed team mascot known for energizing crowds at their NBA games.
-
D.
Adam Chapman
Adam Chapman is a television producer known for his work on the acclaimed nature documentary series "Our Planet."
-
E.
Peter Chapman
Peter Chapman is a writer and journalist known for his historical and political analyses of global corporations and their impact, including his work on the United Fruit Company.
- 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_69c00825df388190a58742fa9b1aa33d |
completed | March 22, 2026, 3:17 p.m. |
| NER | Named-entity recognition | batch_69c022d2ed648190a5152c8668cbda02 |
completed | March 22, 2026, 5:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c04d90c04881908740fb1089c5248a |
completed | March 22, 2026, 8:14 p.m. |
Created at: March 22, 2026, 3:42 p.m.