Triple
T3955961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamlet (stage performances) |
E84977
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object | Ophelia |
E250251
|
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: Ophelia | Statement: [Hamlet (stage performances), hasCharacter, Ophelia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ophelia Context triple: [Hamlet (stage performances), hasCharacter, Ophelia]
-
A.
Ophelia
Ophelia is a famous 1894 Pre-Raphaelite painting by John William Waterhouse depicting the tragic Shakespearean heroine from Hamlet.
-
B.
Ophelia
Ophelia is a famous 1851–52 painting by John Everett Millais, emblematic of the Pre-Raphaelite movement and depicting Shakespeare’s tragic heroine floating in a stream surrounded by lush, detailed flora.
-
C.
Ophelia
chosen
Ophelia is a fictional character best known as the tragic, doomed heroine of William Shakespeare’s play "Hamlet."
-
D.
Ophelia
Ophelia is a savvy and resourceful sex worker in the 1983 comedy film "Trading Places," who helps the protagonist navigate his sudden reversal of fortune.
-
E.
Ofelia
Ofelia is the imaginative young girl in Guillermo del Toro’s dark fantasy film "Pan’s Labyrinth," whose encounters with mythical creatures mirror the brutal realities of post–Civil War Spain.
- 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_69aed934fbfc8190847068e4546de963 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef93f3ad48190b96b98b4aecd6030 |
completed | March 9, 2026, 4:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b533aea08c8190b83d83e3ba89848c |
completed | March 14, 2026, 10:08 a.m. |
Created at: March 9, 2026, 3:30 p.m.