Triple
T712969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Willow |
E14248
|
entity |
| Predicate | antagonist |
P4675
|
FINISHED |
| Object |
Queen Bavmorda
Queen Bavmorda is the ruthless and power-hungry sorceress-queen who serves as the primary villain in the fantasy film "Willow."
|
E86510
|
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: Queen Bavmorda | Statement: [Willow, antagonist, Queen Bavmorda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Queen Bavmorda Context triple: [Willow, antagonist, Queen Bavmorda]
-
A.
Queen Red
Queen Red was one of the designated assault sub-sectors of Sword Beach used by Allied forces during the D-Day landings in World War II.
-
B.
Narsai
Narsai was a prominent 5th-century Syriac Christian theologian and poet, renowned for his extensive homilies and influential role in the Church of the East.
-
C.
Princess May
Princess May, better known as Mary of Teck, was Queen consort of the United Kingdom as the wife of King George V and the mother of Kings Edward VIII and George VI.
-
D.
Maria Magdalena Keverich
Maria Magdalena Keverich was a German woman best known as the mother of the composer Ludwig van Beethoven.
-
E.
Skadi
Skadi is a giantess and goddess in Norse mythology associated with winter, skiing, mountains, and hunting.
- 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: Queen Bavmorda Triple: [Willow, antagonist, Queen Bavmorda]
Generated description
Queen Bavmorda is the ruthless and power-hungry sorceress-queen who serves as the primary villain in the fantasy film "Willow."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Queen Bavmorda Target entity description: Queen Bavmorda is the ruthless and power-hungry sorceress-queen who serves as the primary villain in the fantasy film "Willow."
-
A.
Queen Red
Queen Red was one of the designated assault sub-sectors of Sword Beach used by Allied forces during the D-Day landings in World War II.
-
B.
Narsai
Narsai was a prominent 5th-century Syriac Christian theologian and poet, renowned for his extensive homilies and influential role in the Church of the East.
-
C.
Princess May
Princess May, better known as Mary of Teck, was Queen consort of the United Kingdom as the wife of King George V and the mother of Kings Edward VIII and George VI.
-
D.
Maria Magdalena Keverich
Maria Magdalena Keverich was a German woman best known as the mother of the composer Ludwig van Beethoven.
-
E.
Skadi
Skadi is a giantess and goddess in Norse mythology associated with winter, skiing, mountains, and hunting.
- F. None of above. chosen
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_69a4934a36e081909e7abef98b898a4e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a55ee4fc81909358659ec3bc435f |
completed | March 1, 2026, 8:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a63757e5848190b7c11820f67b20a7 |
completed | March 3, 2026, 1:20 a.m. |
| NEDg | Description generation | batch_69a63a3e81688190ab49d55fb53bfb00 |
completed | March 3, 2026, 1:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a63ae6b6b88190aa2bb2e39b7afff6 |
completed | March 3, 2026, 1:35 a.m. |
Created at: March 1, 2026, 7:36 p.m.