Triple
T16598677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iliou Persis |
E403274
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object |
Helen
Helen is the legendary queen of Sparta whose abduction by Paris sparked the Trojan War in Greek mythology.
|
E145584
|
NE FINISHED |
How this triple was built (4 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 | Statement: [Iliou Persis, featuresCharacter, Helen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Helen Context triple: [Iliou Persis, featuresCharacter, Helen]
-
A.
Helen
Helen is a central character in Ernest Hemingway’s short story “The Snows of Kilimanjaro,” portrayed as the wealthy, devoted wife and companion of the writer Harry during his final, reflective days in Africa.
-
B.
Helen
Helen is the given name of H. T. Lowe-Porter, the American translator best known for bringing Thomas Mann’s works into English.
-
C.
Helen
Helen is the daring, quick-thinking heroine of the early 20th-century silent film serial "The Hazards of Helen," known for her action-packed, stunt-filled adventures.
-
D.
Helen
Helen is the birth name of British television presenter Tess Daly, best known for co-hosting the BBC dance competition show "Strictly Come Dancing."
-
E.
Helen
Helen is a Greek and Danish princess of the early 20th century, known as Princess Helen of Greece and Denmark.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Helen Triple: [Iliou Persis, featuresCharacter, Helen]
Generated description
Helen is the legendary queen of Sparta whose abduction by Paris sparked the Trojan War in Greek mythology.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Helen Target entity description: Helen is the legendary queen of Sparta whose abduction by Paris sparked the Trojan War in Greek mythology.
-
A.
Helen
chosen
Helen is a figure from Greek mythology famed for her extraordinary beauty, whose abduction by Paris sparked the Trojan War.
-
B.
Helen
Helen is a Greek and Danish princess of the early 20th century, known as Princess Helen of Greece and Denmark.
-
C.
Helen
Helen is a feminine given name of Greek origin, traditionally associated with beauty and light and popular in many English-speaking countries.
-
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 daring, quick-thinking heroine of the early 20th-century silent film serial "The Hazards of Helen," known for her action-packed, stunt-filled adventures.
- F. None of above.
Provenance (5 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_69d883880d0c81908b5fcd454e767b60 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e35d74738c81909711654cf38af150 |
completed | April 18, 2026, 10:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00759dea5c819083fe9fb7dee37a35 |
completed | May 10, 2026, 12:10 p.m. |
| NEDg | Description generation | batch_6a0076468d588190972639d0a22f0e3e |
completed | May 10, 2026, 12:12 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a007728680c819082a3bd7e84edb2b0 |
completed | May 10, 2026, 12:16 p.m. |
Created at: April 10, 2026, 5:16 a.m.