Triple
T15452365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Willow Sage Hart |
E371683
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Hart |
E55151
|
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: Hart | Statement: [Willow Sage Hart, familyName, Hart]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hart Context triple: [Willow Sage Hart, familyName, Hart]
-
A.
Hart
chosen
Hart is a surname most famously associated with Moss Hart, the acclaimed American playwright and theater director known for works like "You Can't Take It with You" and "Once in a Lifetime."
-
B.
Hart
Hart is a local government district and civil parish area in Hampshire, England, known for its high quality of life and largely rural character.
-
C.
Good Hart
Good Hart is a small unincorporated community and lakeside resort area on the shore of Lake Michigan in northern Michigan.
-
D.
Hood
Hood is an English surname historically associated with notable figures such as the British naval commander Samuel Hood, 1st Viscount Hood.
-
E.
Hood
"Hood" is a novel by Emma Donoghue that explores grief, identity, and a lesbian relationship in contemporary Ireland.
- 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_69d85cc8bd308190886949510b42e764 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03efaf82c81908b464e37ce9c159a |
completed | April 16, 2026, 1:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff21b3c5a481908057e94fd84f3cfc |
completed | May 9, 2026, 11:59 a.m. |
Created at: April 10, 2026, 3:30 a.m.