Triple
T7457406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laura Dewey Lynn Bridgman |
E172160
|
entity |
| Predicate | hasFamilyName |
P18
|
FINISHED |
| Object | Bridgman |
E172160
|
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: Bridgman | Statement: [Laura Dewey Lynn Bridgman, hasFamilyName, Bridgman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bridgman Context triple: [Laura Dewey Lynn Bridgman, hasFamilyName, Bridgman]
-
A.
Bridgman
chosen
Bridgman is a surname most notably associated with American physicist and Nobel laureate Percy Williams Bridgman, a pioneer in high-pressure physics.
-
B.
Bonger
Bonger is a Dutch surname most notably associated with Johanna van Gogh-Bonger, the key figure in preserving and promoting Vincent van Gogh’s artistic legacy.
-
C.
Wyman-Gordon
Wyman-Gordon is an industrial manufacturer known for producing high-strength forged components, particularly for the aerospace and energy industries.
-
D.
Oberholtzer
Oberholtzer is a German-origin surname, often associated with Mennonite and Amish families, that serves as a variant of the Overholt family name.
-
E.
Hufstedler
Hufstedler is the surname of Shirley Hufstedler, a prominent American judge and the first U.S. Secretary of Education.
- 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_69c68a66554c8190add75c65942c0317 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f3b0780881909e645160dd49eb57 |
completed | March 27, 2026, 9:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c83c5bab90819093431470e0e8c0e3 |
completed | March 28, 2026, 8:38 p.m. |
Created at: March 27, 2026, 3:15 p.m.