Triple
T2270112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East Winch |
E50636
|
entity |
| Predicate | ruralCharacter |
P2460
|
FINISHED |
| Object | rural village |
—
|
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: rural village | Statement: [East Winch, ruralCharacter, rural village]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ruralCharacter Context triple: [East Winch, ruralCharacter, rural village]
-
A.
countryTheme
Indicates that something is associated with or represents a thematic focus on a particular country.
-
B.
farmingCharacteristics
Indicates the specific methods, practices, or attributes that characterize how farming is conducted in relation to an entity.
-
C.
traditionalLifestyle
Indicates that an entity follows or maintains long-established customs, practices, and ways of living, typically in contrast to modern or industrialized lifestyles.
-
D.
hasSuburbanCharacter
Indicates that something possesses qualities or features typically associated with suburban areas, such as lower density, residential focus, and car-oriented development.
-
E.
isRural
chosen
Indicates that something is located in, characteristic of, or associated with a countryside or non-urban area.
- 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_69a88b05910c8190a9a2b1ff230c85f9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc39c6ff0819081a07696f1c29990 |
completed | March 7, 2026, 6:20 a.m. |
| PD | Predicate disambiguation | batch_69abbdb7719081909143efa8f48df4e4 |
completed | March 7, 2026, 5:55 a.m. |
Created at: March 4, 2026, 7:48 p.m.