Triple
T14476129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anne-Elisabeth |
E358976
|
entity |
| Predicate | isGivenNameFormOf |
P15846
|
FINISHED |
| Object | Anne |
E267026
|
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: Anne | Statement: [Anne-Elisabeth, isGivenNameFormOf, Anne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anne Context triple: [Anne-Elisabeth, isGivenNameFormOf, Anne]
-
A.
Anne
Anne is the protagonist of "The Darkest Hour," around whom the film’s central conflict and emotional journey revolve.
-
B.
Anne
Anne is the middle name of American actress Julie Anne Smith, better known professionally as Julianne Moore.
-
C.
Anne
Anne is traditionally revered in Christian tradition as the mother of the Virgin Mary and the grandmother of Jesus.
-
D.
Anne
Anne was the Queen of Great Britain and Ireland from 1702 to 1714, the last monarch of the House of Stuart.
-
E.
Anne
chosen
Anne is a female given name of Hebrew origin, commonly used in many European languages and historically borne by numerous queens, saints, and notable women.
- 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_69d827966698819082e140837737501d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91fc1fc48190842b09aa03ba79f8 |
completed | April 14, 2026, 7:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fde163c3488190aac5a8bd769d5564 |
completed | May 8, 2026, 1:13 p.m. |
Created at: April 10, 2026, 1:20 a.m.