Triple
T23975189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | B0K |
E604344
|
entity |
| Predicate | hasMultipleLocalities |
P154098
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [B0K, hasMultipleLocalities, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMultipleLocalities Context triple: [B0K, hasMultipleLocalities, true]
-
A.
hasNumberOfLocalities
Indicates the relationship that specifies how many localities (e.g., towns, districts, or similar administrative units) are associated with a given entity.
-
B.
hasLocalities
Indicates that an entity is associated with, contains, or is linked to one or more specific geographic or administrative local areas.
-
C.
hasTypeOfLocalities
Indicates that an entity is associated with, or classified by, specific types or categories of localities (e.g., urban, rural, suburban).
-
D.
hasUrbanLocalities
Indicates that an entity possesses or includes one or more urban localities within its jurisdiction or scope.
-
E.
hasMultipleCitiesWithSameName
Indicates that within a given context or region, there exist two or more distinct cities that share the same name.
- 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_69e29543f40c819087700b7a272afb60 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f1d2ba11708190b8587bd006249ff5 |
completed | April 29, 2026, 9:43 a.m. |
| PD | Predicate disambiguation | batch_69f161578d54819084a8b35496299993 |
completed | April 29, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f167dca3608190ace9d2eef56b2af6 |
completed | April 29, 2026, 2:07 a.m. |
Created at: April 17, 2026, 9:26 p.m.