Triple
T18562515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martha Hennessy |
E453680
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Martha Hennessy |
—
|
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: Martha Hennessy | Statement: [Martha Hennessy, name, Martha Hennessy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Martha Hennessy Context triple: [Martha Hennessy, name, Martha Hennessy]
-
A.
Martha Hennessy
chosen
Martha Hennessy is an American Catholic peace activist and granddaughter of Dorothy Day, known for her involvement in the Catholic Worker Movement and anti-nuclear protests.
-
B.
Martha Byrne
Martha Byrne is an American actress best known for her long-running, Emmy-winning role as Lily Walsh Snyder on the soap opera "As the World Turns."
-
C.
Teresa Hennessy
Teresa Hennessy is the child of Tamar Teresa Day Hennessy.
-
D.
Mary Heneghan
Mary Heneghan is best known as the wife of renowned British broadcaster and talk show host Michael Parkinson.
-
E.
Elizabeth McLaughlin
Elizabeth McLaughlin is an American actress known for her roles in television series such as the psychological drama "Hand of God."
- 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_69d8d38974308190a9174430ef256b73 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53afb4f088190adf0b2b64057a210 |
completed | April 19, 2026, 8:28 p.m. |
Created at: April 10, 2026, 11:42 a.m.