Triple
T2985245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seth Low |
E80608
|
entity |
| Predicate | parent |
P120
|
FINISHED |
| Object | Abiel Abbot Low |
E316465
|
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: Abiel Abbot Low | Statement: [Seth Low, parent, Abiel Abbot Low]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Abiel Abbot Low Context triple: [Seth Low, parent, Abiel Abbot Low]
-
A.
Abiel Abbot Low
chosen
Abiel Abbot Low was a prominent 19th-century American China trade merchant and philanthropist who played a key role in the economic and civic development of Brooklyn, New York.
-
B.
H. T. Lowe-Porter
H. T. Lowe-Porter was an American translator best known for introducing English-speaking audiences to the works of German novelist Thomas Mann.
-
C.
Edward Mills
Edward Mills was a British architect known for designing the International Maritime Organization (IMO) Headquarters in London.
-
D.
Maria Bissell Hotchkiss
Maria Bissell Hotchkiss was an American philanthropist best known for endowing and establishing the prestigious Hotchkiss School in Lakeville, Connecticut.
-
E.
Amabel James
Amabel James is known as the spouse of British businessman and hedge fund manager Tony James.
- 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_69ad8b16c3488190b47b6aa7a59a335b |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad99c65ad0819087bb4ae92ab0dc55 |
completed | March 8, 2026, 3:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b12e31a8188190bd5ad6c9757e7141 |
completed | March 11, 2026, 8:56 a.m. |
Created at: March 8, 2026, 2:59 p.m.