Triple
T20967555
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LAU |
E516408
|
entity |
| Predicate | LAU1TypicallyCorrespondsTo |
P28425
|
FINISHED |
| Object | larger local administrative units |
—
|
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: larger local administrative units | Statement: [LAU, LAU1TypicallyCorrespondsTo, larger local administrative units]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: LAU1TypicallyCorrespondsTo Context triple: [LAU, LAU1TypicallyCorrespondsTo, larger local administrative units]
-
A.
allyType
Indicates that one entity is classified as a specific type or category of ally in relation to another entity.
-
B.
lapType
Indicates the specific category or kind of lap being performed or recorded within an activity or event.
-
C.
ATUType
Indicates a classification relationship where an item is assigned a specific Aarne–Thompson–Uther (ATU) folktale type.
-
D.
linguisticType
Indicates the type or category of language or linguistic system associated with an entity (e.g., spoken, signed, written, or other linguistic modality).
-
E.
associatedUnitType
chosen
Indicates that one entity is linked to or characterized by a particular type or category of unit.
- 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_69e0b4fde6c48190af1398e7e734629e |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6fb9d6b548190af7214ad2468cfbf |
completed | April 21, 2026, 4:22 a.m. |
| PD | Predicate disambiguation | batch_69e5dbe6976081908abd4e9c8734bae9 |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 16, 2026, 1:37 p.m.