Triple
T4736845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trojan Women |
E105145
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Helen |
E145584
|
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 | Statement: [Trojan Women, featuresCharacter, Helen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Helen Context triple: [Trojan Women, featuresCharacter, Helen]
-
A.
Helen
Helen is the birth name of Beatrix Potter, the renowned English writer and illustrator best known for her children's books featuring animal characters such as Peter Rabbit.
-
B.
Helen
chosen
Helen is a figure from Greek mythology famed for her extraordinary beauty, whose abduction by Paris sparked the Trojan War.
-
C.
Helen
Helen is the mute, terrorized heroine of the classic 1946 psychological thriller film "The Spiral Staircase."
-
D.
Helen
Helen is the given first name of Violet Bonham Carter, a prominent British Liberal politician and orator of the 20th century.
-
E.
Helen
Helen is a character in Aldous Huxley’s novel "Eyeless in Gaza," representing one of the key figures in the book’s exploration of memory, morality, and personal transformation.
- 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_69bd43ee52048190b81a4f066534ffb3 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd64831c58819098758ac1f7839b3a |
completed | March 20, 2026, 3:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be3a1796608190972865b2f6beef05 |
completed | March 21, 2026, 6:26 a.m. |
Created at: March 20, 2026, 1:19 p.m.