Triple
T25938909
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen Gayelette |
E653636
|
entity |
| Predicate | reasonForEnchantingWingedMonkeys |
P169538
|
FINISHED |
| Object | punishment for spoiling Quelala’s wedding clothes |
—
|
LITERAL 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: punishment for spoiling Quelala’s wedding clothes | Statement: [Queen Gayelette, reasonForEnchantingWingedMonkeys, punishment for spoiling Quelala’s wedding clothes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForEnchantingWingedMonkeys Context triple: [Queen Gayelette, reasonForEnchantingWingedMonkeys, punishment for spoiling Quelala’s wedding clothes]
-
A.
hasWingsMadeOf
Indicates that one entity has wings whose material or composition is made from the other entity.
-
B.
enchantedInto
Indicates that one entity is magically transformed or turned into another entity through enchantment.
-
C.
enchantedTo
Indicates that one entity has been magically imbued or altered so that it possesses a special effect, property, or behavior caused by another entity.
-
D.
hasWings
Indicates that an entity possesses wings as physical appendages.
-
E.
enchantedBy
Indicates that one entity has cast or holds a magical enchantment over another entity.
- F. None of above. chosen
Provenance (4 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_69e7ab3fd2f881908837305e4ba98011 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f67fc237608190b6542b56038a7fe4 |
completed | May 2, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_69f67e3ed894819094c067c1ef624951 |
completed | May 2, 2026, 10:44 p.m. |
| PDg | Predicate description generation | batch_69f67f0353c88190a05b2db449abe0f4 |
completed | May 2, 2026, 10:47 p.m. |
Created at: April 22, 2026, 8:40 a.m.