Triple
T4895637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sorrow |
E109669
|
entity |
| Predicate | hasRelationshipWith |
P2830
|
FINISHED |
| Object | Lina |
E109668
|
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: Lina | Statement: [Sorrow, hasRelationshipWith, Lina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lina Context triple: [Sorrow, hasRelationshipWith, Lina]
-
A.
Lina
chosen
Lina is a Native American servant in Toni Morrison’s novel *A Mercy*, whose history of displacement and resilience reflects the novel’s themes of slavery, colonialism, and survival in 17th-century America.
-
B.
Lucina
Lucina is a woman known primarily as the mother of the Western Roman Emperor Anthemius.
-
C.
Lilia
Lilia is a feminine given name, often considered a variant of Lily and associated with the elegance and symbolism of the lily flower.
-
D.
D'Lila
D'Lila is one of the twin daughters of music mogul Sean "Diddy" Combs and the late model Kim Porter.
-
E.
Marzelline
Marzelline is a character in Beethoven's opera "Fidelio," portrayed as the jailer Rocco’s daughter who becomes romantically entangled with the disguised heroine.
- 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_69bd4410bbf88190aad50d2451c863d6 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6e27cdf48190bb9bd13bd25b887e |
completed | March 20, 2026, 3:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be6fc665e08190ae067746d6c19018 |
completed | March 21, 2026, 10:15 a.m. |
Created at: March 20, 2026, 1:28 p.m.