Triple
T5813510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Waverley Abbey |
E128926
|
entity |
| Predicate | hasRemainsCondition |
P1255
|
FINISHED |
| Object | ruined |
—
|
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: ruined | Statement: [Waverley Abbey, hasRemainsCondition, ruined]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRemainsCondition Context triple: [Waverley Abbey, hasRemainsCondition, ruined]
-
A.
hasRemainsOf
Indicates that one entity physically contains, preserves, or is associated with the leftover physical traces or remnants of another entity.
-
B.
hasCondition
chosen
Indicates that an entity possesses, experiences, or is affected by a particular condition or state.
-
C.
hasNumberOfConditions
Indicates that an entity is associated with a specific count of conditions it has or is subject to.
-
D.
hasContinuation
Indicates that one entity serves as a continuation or subsequent part of another entity in a sequence or process.
-
E.
hasCurrent
Indicates that an entity presently possesses, exhibits, or is associated with a particular state, attribute, or resource at the current time.
- 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_69c0084788848190bcf71f6bc5d71597 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0400f1af881908d376ea4793f6dea |
completed | March 22, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_69c0333fdd7081908d829265caa2ac11 |
completed | March 22, 2026, 6:21 p.m. |
Created at: March 22, 2026, 3:52 p.m.