Triple
T9914697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donovan's Brain |
E185837
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Lisa Howard |
E351187
|
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: Lisa Howard | Statement: [Donovan's Brain, stars, Lisa Howard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lisa Howard Context triple: [Donovan's Brain, stars, Lisa Howard]
-
A.
Lisa Howard
chosen
Lisa Howard was an American actress active in the mid-20th century, known for her work in film, television, and theater.
-
B.
Jennifer Howard
Jennifer Howard was an American actress and the daughter of playwright Sidney Howard and actress Clare Eames, known for her work on stage and screen in the mid-20th century.
-
C.
Emily Lloyd
Emily Lloyd is a British actress best known for her acclaimed breakthrough role in the 1987 film "Wish You Were Here."
-
D.
Lisa Harriton
Lisa Harriton is an American singer-songwriter, keyboardist, and composer best known for her work in pop and film music, including contributions to hit songs from "The Lego Movie."
-
E.
Elizabeth Harrison
Elizabeth Harrison was an American educator and early childhood education pioneer who helped professionalize kindergarten teaching in the United States.
- 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_69ca829b45f481909040f7b99a1976ed |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cdb53ba1ac8190ba655133b81596d7 |
completed | April 2, 2026, 12:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d32a6ee36881909aabd35a77e62918 |
completed | April 6, 2026, 3:37 a.m. |
Created at: March 30, 2026, 8:41 p.m.