Triple
T13018507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skitch Henderson |
E322613
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Faye Emerson |
E67606
|
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: Faye Emerson | Statement: [Skitch Henderson, spouse, Faye Emerson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Faye Emerson Context triple: [Skitch Henderson, spouse, Faye Emerson]
-
A.
Faye Emerson
chosen
Faye Emerson was an American film and stage actress who became a popular early television personality in the 1940s and 1950s.
-
B.
Faye Miller
Faye Miller is a market research psychologist who becomes one of Don Draper’s significant romantic partners in the television series "Mad Men."
-
C.
Faye Medwick
Faye Medwick is a fictional character appearing in the work titled "Chapter Two."
-
D.
Faye Ward
Faye Ward is a British film and television producer known for her work on acclaimed projects such as the historical drama "Suffragette."
-
E.
Faye Webb Gardner
Faye Webb Gardner was a prominent local benefactor and namesake whose support and influence were instrumental in the development of Gardner–Webb Junior College in North Carolina.
- 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_69d807657e8c8190bd9435ee2f823845 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97ece22908190a0941e23df7c774d |
completed | April 10, 2026, 10:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75d7cfe24819096e8f4cd496a6fd7 |
completed | May 3, 2026, 2:36 p.m. |
Created at: April 9, 2026, 8:51 p.m.