Triple
T11743295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Troy Book |
E279206
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Helen of Troy |
E24191
|
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: Helen of Troy | Statement: [The Troy Book, featuresCharacter, Helen of Troy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Helen of Troy Context triple: [The Troy Book, featuresCharacter, Helen of Troy]
-
A.
Helen of Troy
chosen
Helen of Troy is a legendary figure from Greek mythology renowned as the most beautiful woman in the world, whose abduction by Paris sparked the Trojan War.
-
B.
Athénaïs
Athénaïs was the familiar name of Madame de Montespan, the influential chief mistress of King Louis XIV of France and a prominent figure at the 17th-century French court.
-
C.
Helen
Helen is the birth name of P. L. Travers, the Australian-British author best known for creating the "Mary Poppins" series.
-
D.
Helen
Helen is a fictional protagonist associated with a narrative set in or around New York City's Central Park.
-
E.
Helen
Helen is the given name of Maria Helen Van Schaack, likely used as her primary personal name.
- 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_69d6ab01038c819080714901502c84fc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4f191388190bd6ef7e80c41ca48 |
completed | April 10, 2026, 7:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f019e4f0988190afe0b92f4c9d8073 |
completed | April 28, 2026, 2:22 a.m. |
Created at: April 8, 2026, 9:41 p.m.