Triple
T10273124
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Louisa Gummer |
E240888
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Gummer |
E240888
|
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: Gummer | Statement: [Louisa Gummer, familyName, Gummer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gummer Context triple: [Louisa Gummer, familyName, Gummer]
-
A.
Gummer
chosen
Gummer is a surname most notably associated with American sculptor Don Gummer and his family.
-
B.
Gardell
Gardell is a Swedish surname most notably associated with comedian, author, and playwright Jonas Gardell.
-
C.
Gruer
Gruer is a character in Isaac Asimov's science fiction novel "The Naked Sun," involved in the investigation central to the story's plot.
-
D.
Bricklebaum
Bricklebaum is a relentlessly cheerful and friendly Whoville resident who tries to befriend the Grinch in the 2018 animated adaptation of Dr. Seuss's classic story.
-
E.
Gussie
Gussie is a fictional character best known as the hapless young protagonist in P. G. Wodehouse’s comic story “Extricating Young Gussie.”
- 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_69d381a94c1881908fc38fc263d9b9c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d288acf48190bbf14a5cb2dfe1f4 |
completed | April 7, 2026, 9:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d87e40205c8190a4788e1db1f149d2 |
completed | April 10, 2026, 4:36 a.m. |
Created at: April 6, 2026, 11:36 a.m.