Triple
T9494504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nellie Connally |
E228969
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Nellie |
E228968
|
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: Nellie | Statement: [Nellie Connally, givenName, Nellie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nellie Context triple: [Nellie Connally, givenName, Nellie]
-
A.
Nellie
chosen
Nellie is the familiar nickname of Nellie Connally, the former First Lady of Texas who was riding in the car with President John F. Kennedy during his assassination in 1963.
-
B.
Nellie Bellflower
Nellie Bellflower is an American actress and film producer best known for producing the acclaimed 2004 film "Finding Neverland."
-
C.
Nellie Lapine
Nellie Lapine is the daughter of acclaimed American theater director and playwright James Lapine.
-
D.
Nell
Nell is a feminine given name, often used as a diminutive of names like Eleanor or Helen.
-
E.
Nellie Riley
Nellie Riley was the longtime wife of legendary UCLA basketball coach John Wooden and an important personal influence throughout his life and career.
- 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_69ca847424f081908180305555139f7a |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd95ea4a04819092c7842361c6296e |
completed | April 1, 2026, 10:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d13a0331e08190b42df462c50e1f44 |
completed | April 4, 2026, 4:19 p.m. |
Created at: March 30, 2026, 7:56 p.m.