Triple
T7125833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beatrice Jean Howard-Gabel |
E166058
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Howard-Gabel |
E429571
|
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: Howard-Gabel | Statement: [Beatrice Jean Howard-Gabel, familyName, Howard-Gabel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Howard-Gabel Context triple: [Beatrice Jean Howard-Gabel, familyName, Howard-Gabel]
-
A.
Howard-Gabel
chosen
Howard-Gabel is a surname associated with individuals such as Theodore Norman Howard-Gabel.
-
B.
Howard & Galloway
Howard & Galloway was an architectural firm known for designing early 20th-century institutional and academic buildings in California.
-
C.
Gabbs
Gabbs is a small, remote town in central Nevada known historically for its mining activities and desert surroundings.
-
D.
Eggers
Eggers is the surname of American writer, editor, and publisher Dave Eggers, known for works like "A Heartbreaking Work of Staggering Genius" and for founding McSweeney’s.
-
E.
Keyserling
Keyserling is a surname most notably associated with Leon H. Keyserling, an influential American economist and former chairman of the U.S. Council of Economic Advisers.
- 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_69c6888350588190870cd552b427a1cd |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e64d99888190a93c1822e19b5457 |
completed | March 27, 2026, 8:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7a3357e548190bb56c31843c69f95 |
completed | March 28, 2026, 9:45 a.m. |
Created at: March 27, 2026, 2:44 p.m.