Triple
T22396346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mason Lee |
E553639
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Lucy |
—
|
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: Lucy | Statement: [Mason Lee, notableWork, Lucy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lucy Context triple: [Mason Lee, notableWork, Lucy]
-
A.
Lucy
Lucy is a NASA Discovery Program space mission designed to study Jupiter’s Trojan asteroids to better understand the early solar system’s formation and evolution.
-
B.
Lucy
"Lucy" is a coming-of-age novella by Jamaica Kincaid that follows a young Caribbean woman navigating identity, colonial legacy, and independence while working as an au pair in the United States.
-
C.
Lucy
chosen
Lucy is a fictional character named in the context of "Loosies," likely serving as a supporting figure in that film’s narrative.
-
D.
Lucy
Lucy is a singer-songwriter and musician best known as a solo indie rock artist and as a member of the supergroup boygenius.
-
E.
Lucy
Lucy is the protagonist of the romance story "Kissing Lessons," around whom the central emotional and narrative developments revolve.
- 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_69e11e4da7048190b4387d422a9a0de5 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1585e84b081908c95ed3e0d987ed8 |
completed | April 29, 2026, 1:01 a.m. |
Created at: April 16, 2026, 8:45 p.m.