Triple
T22366382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nina Hartley |
E552914
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Hartman |
—
|
NE NERFINISHED |
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: Hartman | Statement: [Nina Hartley, familyName, Hartman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hartman Context triple: [Nina Hartley, familyName, Hartman]
-
A.
Hartman
chosen
Hartman is a surname of Germanic origin borne by various notable individuals across fields such as entertainment, academia, and politics.
-
B.
Hartmann
Hartmann is a German surname borne by numerous notable individuals across fields such as music, philosophy, and aviation.
-
C.
Harnell
Harnell is a surname most notably associated with American voice actor and singer Jess Harnell.
-
D.
Hesseman
Hesseman is a surname most notably associated with American actor and comedian Howard Hesseman, known for his role on the television series "WKRP in Cincinnati."
-
E.
Pittman
Pittman is a surname of English origin borne by various notable individuals across politics, sports, and the arts.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e4affcc8190ba7c27d29062558d |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1580074dc819091305ac7017000d3 |
completed | April 29, 2026, 12:59 a.m. |
Created at: April 16, 2026, 8:44 p.m.