Triple
T34999528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mrs. Poyser |
E1009629
|
entity |
| Predicate | setInCounty |
P23957
|
FINISHED |
| Object | Loamshire (fictional English county) |
—
|
NE NERFINISHED |
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: Loamshire (fictional English county) | Statement: [Mrs. Poyser, setInCounty, Loamshire (fictional English county)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: setInCounty Context triple: [Mrs. Poyser, setInCounty, Loamshire (fictional English county)]
-
A.
inCounty
chosen
Indicates that one entity is geographically or administratively located within the boundaries of a specified county.
-
B.
includesCounty
Indicates that a larger geographic or administrative region contains or encompasses a specific county within its boundaries.
-
C.
isInCountySeatCounty
Indicates that a given place is located within the county that serves as the county seat for a specified jurisdiction.
-
D.
hasRankInCounty
Indicates that an entity holds a specific rank or position within the administrative boundaries of a particular county.
-
E.
isInCountySeatOf
Indicates that one entity is located within the town or city that serves as the administrative center (county seat) of a specified county.
- 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_69f76dcb716881909f75e4fd60ab2284 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78ce78b508190955848e133398dc8 |
completed | May 3, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69f78b8f4cc08190b49fccd798cb25d7 |
completed | May 3, 2026, 5:53 p.m. |
Created at: May 3, 2026, 4:01 p.m.