Triple
T18933675
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yu’an District |
E463182
|
entity |
| Predicate | isSeatWithin |
P133855
|
FINISHED |
| Object | Lu’an City urban core |
—
|
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: Lu’an City urban core | Statement: [Yu’an District, isSeatWithin, Lu’an City urban core]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isSeatWithin Context triple: [Yu’an District, isSeatWithin, Lu’an City urban core]
-
A.
isSafeSeatFor
Indicates that one entity is a suitable and secure seating option for another entity, posing no unacceptable risk or harm.
-
B.
hasSeatAt
Indicates that an entity occupies or holds a place, position, or membership within a specific group, body, or location.
-
C.
seatIs
Indicates that one entity functions as the seat or seating position of another entity.
-
D.
hasSeat
Indicates that one entity possesses, provides, or includes a seat for another entity.
-
E.
seatInHierarchy
Indicates that one entity occupies a specific position or level within an ordered hierarchy relative to other entities.
- 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_69d8dcfec90481909e926be9767e5779 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d3e57e648190aa4d3b09e84d4d38 |
completed | April 20, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69e4a2efec5c8190840704016bf547a1 |
completed | April 19, 2026, 9:40 a.m. |
| PDg | Predicate description generation | batch_69e4ad8e075c8190ad561edc5e520057 |
completed | April 19, 2026, 10:25 a.m. |
Created at: April 10, 2026, 11:59 a.m.