Triple
T18555224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Singel |
E453485
|
entity |
| Predicate | isInTimePeriod |
P56370
|
FINISHED |
| Object | Middle Ages (as city moat) |
—
|
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: Middle Ages (as city moat) | Statement: [Singel, isInTimePeriod, Middle Ages (as city moat)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isInTimePeriod Context triple: [Singel, isInTimePeriod, Middle Ages (as city moat)]
-
A.
isSetInTimePeriod
chosen
Indicates that an event, story, or situation takes place within a specified time period.
-
B.
meetsInTimePeriod
Indicates that two entities encounter or come together during a specified time period.
-
C.
timePeriodWithin
Indicates that one time period is entirely contained within the bounds of another time period.
-
D.
timeSpanIncludes
Indicates that one time span fully contains or covers the entire duration of another time span.
-
E.
currentBetween
Indicates that the current value of a quantity lies within a specified range between two boundary values.
- 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_69d8d388b0c881908e610a1c45b52640 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53806046481908efbbe6909b2c68b |
completed | April 19, 2026, 8:16 p.m. |
| PD | Predicate disambiguation | batch_69e469e274a48190a570b25cfef4d890 |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:38 a.m.