Triple
T34430344
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wicklow (town) |
E883808
|
entity |
| Predicate | isCountyTown |
P178937
|
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: [Wicklow (town), isCountyTown, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isCountyTown Context triple: [Wicklow (town), isCountyTown, true]
-
A.
isInCountySeatOf
Indicates that one entity is located within the town or city that serves as the administrative center (county seat) of a specified county.
-
B.
isCountyEquivalentSeatOf
Indicates that a place serves as the administrative seat for a county-equivalent jurisdiction (such as an independent city or similar entity functioning at the county level).
-
C.
containsCountySeat
Indicates that one administrative region or area includes within its boundaries the designated county seat location of a county.
-
D.
hasCountySeatCity
Indicates that a county has a specific city that serves as its official administrative center or county seat.
-
E.
hasCountySeatCounty
Indicates that a county seat is administratively associated with and serves as the seat of government for a specific county.
- 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_69f349c3dd2c819092cc9e64809f4a42 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f719cc31ec819099bebcf833b14d76 |
completed | May 3, 2026, 9:47 a.m. |
| PD | Predicate disambiguation | batch_69f71824431081908d9685d2462ea242 |
completed | May 3, 2026, 9:40 a.m. |
| PDg | Predicate description generation | batch_69f719458378819081725f544efb1173 |
completed | May 3, 2026, 9:45 a.m. |
Created at: May 1, 2026, 2 a.m.