Triple
T20997702
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | High Hopes |
E517192
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Shirley |
—
|
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: Shirley | Statement: [High Hopes, mainCharacter, Shirley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shirley Context triple: [High Hopes, mainCharacter, Shirley]
-
A.
Shirley
Shirley is a small town in north-central Massachusetts served by commuter rail on the MBTA Fitchburg Line.
-
B.
Shirley
"Shirley" is a rock and roll song by Welsh singer Shakin' Stevens, known as one of his early hits.
-
C.
Shirley
chosen
Shirley is one of Count Olaf’s many disguises in Lemony Snicket’s "A Series of Unfortunate Events," used as part of his schemes against the Baudelaire orphans.
-
D.
Shirley
Shirley is the given name of Shirley Ann Jackson, a prominent American physicist and trailblazing academic leader.
-
E.
Shirley
"Shirley" is a social and political novel by Charlotte Brontë set during the industrial unrest of early 19th-century England, exploring themes of class conflict, gender roles, and economic hardship.
- 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_69e0b5006e2881909fc2383f841740cc |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc22ca6081908bf054ddcfea9e19 |
completed | April 21, 2026, 4:25 a.m. |
Created at: April 16, 2026, 1:51 p.m.