Triple
T1747130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Olivia Langdon Clemens |
E38359
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Olivia |
E52448
|
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: Olivia | Statement: [Olivia Langdon Clemens, givenName, Olivia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Olivia Context triple: [Olivia Langdon Clemens, givenName, Olivia]
-
A.
Olivia
chosen
Olivia is a feminine given name of Latin origin meaning "olive tree," widely used in English-speaking countries and popularized by literature and modern media.
-
B.
Chloe
Chloe is an epithet of the Greek goddess Demeter, highlighting her aspect as the bringer of new green growth and flourishing vegetation.
-
C.
Chloe
Chloe is the birth name of Nobel Prize–winning American novelist Toni Morrison, renowned for her powerful explorations of African American life and history.
-
D.
Olivia Mariamne Devenish
Olivia Mariamne Devenish was the first wife of British colonial administrator Sir Thomas Stamford Raffles and accompanied him during his early career in Southeast Asia.
-
E.
Mia
Mia is a major fine art museum in Minneapolis, Minnesota, known for its extensive and diverse collection spanning thousands of years and cultures.
- 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_69a8862b01a48190ab47209063af82d9 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa63eabdf48190878ecde3d1b1faf3 |
completed | March 6, 2026, 5:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ada0e058948190939e936af8f0e221 |
completed | March 8, 2026, 4:16 p.m. |
Created at: March 4, 2026, 7:31 p.m.