Triple
T16248676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tippi Hedren |
E394440
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Nathalie |
E1127849
|
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: Nathalie | Statement: [Tippi Hedren, givenName, Nathalie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nathalie Context triple: [Tippi Hedren, givenName, Nathalie]
-
A.
Nathalie
chosen
Nathalie is a feminine given name of French origin commonly used in many European and French-speaking countries.
-
B.
Léa
Léa is a French feminine given name commonly used in Francophone countries.
-
C.
Mélanie
Mélanie is a feminine given name of French origin commonly used in French-speaking countries.
-
D.
Stéphanie
Stéphanie is a Monegasque princess, singer, and fashion designer, best known as the youngest child of Prince Rainier III and Grace Kelly.
-
E.
Laetitia
Laetitia is a feminine given name of Latin origin, historically borne by figures such as the English poet and essayist Anna Laetitia Barbauld.
- 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_69d87f2171208190951025e526947816 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e24594f23c8190bd59fcb2585cb5e3 |
completed | April 17, 2026, 2:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0017b1e22c8190bddca67661121c2d |
completed | May 10, 2026, 5:29 a.m. |
Created at: April 10, 2026, 5:04 a.m.