Triple
T21435504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | There Was a Queen |
E528796
|
entity |
| Predicate | recurringElements |
P10543
|
FINISHED |
| Object | Old South aristocracy |
—
|
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: Old South aristocracy | Statement: [There Was a Queen, recurringElements, Old South aristocracy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recurringElements Context triple: [There Was a Queen, recurringElements, Old South aristocracy]
-
A.
featuresRecurringElement
Indicates that something includes an element, motif, or component that appears repeatedly over time or across multiple instances.
-
B.
hasRecurringElement
chosen
Indicates that an entity includes an element that appears repeatedly or occurs multiple times within it.
-
C.
recurringSeries
Indicates that an event, action, or pattern occurs repeatedly over time as part of an ongoing series rather than as a one-time instance.
-
D.
recurringDuring
Indicates that an event or state happens repeatedly within the time span or context defined by another event or interval.
-
E.
recurringEvent
Indicates that an event occurs repeatedly over time according to some regular pattern or schedule.
- 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_69e0c4569fa081908101baa24f8745db |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e8b536274c8190809bd3cdf4ef899e |
completed | April 22, 2026, 11:47 a.m. |
| PD | Predicate disambiguation | batch_69e61639ee288190889ffd500d1260f6 |
completed | April 20, 2026, 12:04 p.m. |
Created at: April 16, 2026, 6:02 p.m.