Triple
T836806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Corsair |
E18085
|
entity |
| Predicate | relatedWorkBySameAuthor |
P13484
|
FINISHED |
| Object | Lara |
E77944
|
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: Lara | Statement: [The Corsair, relatedWorkBySameAuthor, Lara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lara Context triple: [The Corsair, relatedWorkBySameAuthor, Lara]
-
A.
Lara
chosen
Lara is a feminine given name, often used in various cultures and languages, sometimes as a variant of Laura or derived from Latin and Russian origins.
-
B.
Sheena
Sheena is the first name of Scottish singer and actress Sheena Easton, known for hits in the 1980s such as "Morning Train (Nine to Five)" and "For Your Eyes Only."
-
C.
Diana
Diana is a feminine given name of Latin origin, famously borne by the Roman goddess of the hunt and by Diana, Princess of Wales.
-
D.
Rachel
Rachel is a prominent biblical matriarch in the Book of Genesis, known as Jacob’s beloved wife and the mother of Joseph and Benjamin.
-
E.
Zora
Zora is a feminine given name most famously associated with the African-American author and anthropologist Zora Neale Hurston.
- 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_69a49389f44881909a608fb27d89f247 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b2b66c908190a52f731119b77a1e |
completed | March 1, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7929624e88190bb7e1c644b8cc52b |
completed | March 4, 2026, 2:01 a.m. |
Created at: March 1, 2026, 7:38 p.m.