Triple
T34045075
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tullie Smith House |
E873064
|
entity |
| Predicate | hasLivestockArea |
P30553
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Tullie Smith House, hasLivestockArea, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLivestockArea Context triple: [Tullie Smith House, hasLivestockArea, yes]
-
A.
hasPastoralArea
Indicates that one entity is assigned to, responsible for, or associated with a specific pastoral area or pastoral care region of another entity.
-
B.
hasPaddock
chosen
Indicates that one entity possesses or is associated with a specific paddock area or enclosure.
-
C.
hasFarm
Indicates that one entity owns, operates, or is responsible for a farm associated with another entity.
-
D.
hasAgriculturalFacility
Indicates that an entity possesses, contains, or is associated with an agricultural facility used for farming, cultivation, or related agricultural operations.
-
E.
useOfLivestock
Indicates the action or practice of employing livestock for a particular purpose or function.
- 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_69f349a3363081909cea4c9a848cefe2 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fe68a4b67881909ca1d9f276f922e0 |
completed | May 8, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_69fe680234c88190b01f953987b74972 |
completed | May 8, 2026, 10:47 p.m. |
Created at: May 1, 2026, 1:51 a.m.