Triple
T28839431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fantastic Beasts and Where to Find Them |
E728272
|
entity |
| Predicate | containsEntryType |
P79568
|
FINISHED |
| Object | beast entries |
—
|
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: beast entries | Statement: [Fantastic Beasts and Where to Find Them, containsEntryType, beast entries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsEntryType Context triple: [Fantastic Beasts and Where to Find Them, containsEntryType, beast entries]
-
A.
hasEntryType
chosen
Indicates that something is associated with a specific category or type of entry within a system or dataset.
-
B.
hasEntryOn
Indicates that one entity contains or includes an entry, record, or listing about another entity.
-
C.
hasElementType
Indicates that something is composed of or contains elements that are of a specified type.
-
D.
hasEntryExample
Indicates that something includes or is associated with a specific example illustrating one of its entries.
-
E.
hasContainmentType
Indicates the specific way in which one entity is contained within or enclosed by another.
- 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_69fddd373cdc8190be1b12e70e4deb1f |
completed | May 8, 2026, 12:55 p.m. |
| PD | Predicate disambiguation | batch_69fddc6915a88190ad41e379aa3ede13 |
completed | May 8, 2026, 12:51 p.m. |
Created at: April 28, 2026, 6:40 a.m.