Triple
T16627862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Countess Eloise of Oranje-Nassau |
E403997
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Eloise |
E698803
|
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: Eloise | Statement: [Countess Eloise of Oranje-Nassau, givenName, Eloise]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eloise Context triple: [Countess Eloise of Oranje-Nassau, givenName, Eloise]
-
A.
Eloise
chosen
Eloise is a spirited, mischievous little girl who lives in New York’s Plaza Hotel and stars in Kay Thompson’s classic children’s book series.
-
B.
Eloise
Eloise is the given first name of American actress Isabel Sanford, best known for her role as Louise "Weezy" Jefferson on the sitcom The Jeffersons.
-
C.
Louise
Louise is a feminine given name of French origin, traditionally associated with nobility and widely used in many European and English-speaking countries.
-
D.
Louise
Louise is an opera by French composer Gustave Charpentier, renowned for its realistic portrayal of Parisian working-class life and its influential role in early 20th-century French opera.
-
E.
Aloise
Aloise is a given name, most notably borne by Aloise Steiner Buckley.
- 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_69d883897eb481909eaaa088ba9918d9 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e378e2683481908c9a5ed895a09a6e |
completed | April 18, 2026, 12:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a007dba91bc819090a78ac4c0c01fc8 |
completed | May 10, 2026, 12:44 p.m. |
Created at: April 10, 2026, 5:17 a.m.