Triple
T28840049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Snatchers |
E728288
|
entity |
| Predicate | deliveredPrisonersTo |
P74412
|
FINISHED |
| Object | Malfoy Manor |
—
|
NE NERFINISHED |
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: Malfoy Manor | Statement: [Snatchers, deliveredPrisonersTo, Malfoy Manor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: deliveredPrisonersTo Context triple: [Snatchers, deliveredPrisonersTo, Malfoy Manor]
-
A.
detainedPrisonersFrom
Indicates that an authority is holding prisoners who originate from or are associated with a specified place or source.
-
B.
receivesPrisonersFrom
chosen
Indicates that one entity accepts or takes custody of prisoners who are transferred from another entity.
-
C.
carriedPrisonersFrom
Indicates that an entity transported prisoners away from a specified origin location or source.
-
D.
hasPrisoners
Indicates that an entity holds or contains one or more individuals who are imprisoned or detained.
-
E.
numberOfConvictsCarried
Indicates the quantity of convicts that were transported or carried in a given context or event.
- F. None of above.
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_69f0319e8e7c8190b37288c8845b9dbc |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f65b14512c8190a40e70319dcc54cd |
completed | May 2, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69f659d02f1c8190831758ac52bb54e4 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 28, 2026, 6:40 a.m.