Triple
T8777889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elizabeth Coombs Adams |
E208641
|
entity |
| Predicate | mother |
P120
|
FINISHED |
| Object | Ann Harrod |
E61743
|
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: Ann Harrod | Statement: [Elizabeth Coombs Adams, mother, Ann Harrod]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ann Harrod Context triple: [Elizabeth Coombs Adams, mother, Ann Harrod]
-
A.
Ann Harrod
chosen
Ann Harrod was the wife of Thomas Boylston Adams, a lawyer and the youngest son of U.S. President John Adams.
-
B.
Lissa Evans
Lissa Evans is a British author and former television director and producer, known for her witty, character-driven novels for both adults and children.
-
C.
Ann Hould-Ward
Ann Hould-Ward is a Tony Award–winning American costume designer renowned for her work on major Broadway productions, including Disney’s stage adaptation of Beauty and the Beast.
-
D.
Kate Harwood
Kate Harwood is a British television producer and executive known for her work on high-profile drama series, including the acclaimed crime drama "Luther."
-
E.
Belinda Bauer
Belinda Bauer is an Australian actress best known for her film and television roles in the 1980s and early 1990s, often in thrillers and science fiction projects.
- 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_69ca835fbee88190bf625939bac48d7f |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5f51b3d48190b542a0423d3938e0 |
completed | March 31, 2026, 11:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf51d69af481909245ca327f36e9c2 |
completed | April 3, 2026, 5:36 a.m. |
Created at: March 30, 2026, 6:42 p.m.