Triple
T15160122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andrea Leeds |
E362187
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Antoinette |
E182168
|
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: Antoinette | Statement: [Andrea Leeds, givenName, Antoinette]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Antoinette Context triple: [Andrea Leeds, givenName, Antoinette]
-
A.
Antoinette
chosen
Antoinette is a feminine given name of French origin, historically associated with nobility and later borne by various notable figures in the arts and public life.
-
B.
Antoinette
Antoinette is the birth name of Princess Muna al-Hussein, the British-born mother of King Abdullah II of Jordan.
-
C.
Lucienne
Lucienne is a feminine given name of French origin, traditionally used in Francophone countries.
-
D.
Renée
Renée is a feminine given name of French origin, commonly used in French-speaking countries and beyond.
-
E.
Arlette
Arlette, also known as Herleva of Falaise, was the mother of William the Conqueror and a key figure in the early life of the first Norman king of England.
- 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_69d85a087b7c81908baa94a53dac8d68 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0060dd71881908ecc4a4f52d438a5 |
completed | April 15, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3d3b3fc0819094daf892200bd1ac |
completed | May 9, 2026, 1:57 p.m. |
Created at: April 10, 2026, 3:08 a.m.