Triple
T872408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Isabel Allende |
E18842
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Paula |
E40562
|
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: Paula | Statement: [Isabel Allende, notableWork, Paula]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paula Context triple: [Isabel Allende, notableWork, Paula]
-
A.
Paula
chosen
Paula is a feminine given name used in many languages, derived from the Latin name Paulus meaning "small" or "humble."
-
B.
Patricia
Patricia is a feminine given name of Latin origin, commonly used in English-speaking countries.
-
C.
Marcia
Marcia was the mother of the Roman emperor Trajan and a member of the provincial Roman aristocracy in Hispania.
-
D.
Rachele
Rachele is an Italian given name, notably borne by Rachele Mussolini, the wife of dictator Benito Mussolini.
-
E.
Jacqueline
Jacqueline is a feminine given name most famously borne by former U.S. First Lady Jacqueline Kennedy Onassis.
- 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_69a4938db1f081909bcd1ad2713b6096 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac96850881908a2d776685126137 |
completed | March 1, 2026, 9:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac762e945c8190a4716a2115689b20 |
completed | March 7, 2026, 7:02 p.m. |
Created at: March 1, 2026, 7:39 p.m.