Triple
T5741972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jane Banks |
E126635
|
entity |
| Predicate | timeSettingOfMaryPoppinsReturns |
P20835
|
FINISHED |
| Object | 1930s London |
—
|
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: 1930s London | Statement: [Jane Banks, timeSettingOfMaryPoppinsReturns, 1930s London]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeSettingOfMaryPoppinsReturns Context triple: [Jane Banks, timeSettingOfMaryPoppinsReturns, 1930s London]
-
A.
timeOfSetting
chosen
Indicates the specific time at which an event, object, or phenomenon is set, scheduled, or takes place.
-
B.
timeDefinite
Indicates that the associated event or state occurs at a clearly specified, fixed point or interval in time.
-
C.
timeType
Indicates the specific temporal category or classification associated with a time-related entity or value (e.g., duration, point in time, interval, or recurrence type).
-
D.
timeStructure
Indicates that one entity defines, constrains, or organizes the temporal framework or schedule within which another entity exists or operates.
-
E.
timeStatus
Indicates the temporal state or condition of an event or entity relative to a reference time (e.g., past, present, future, ongoing, or scheduled).
- 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_69c0083179548190b384b0bf3c08ca4d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02b52663c8190ab44258468d4296d |
completed | March 22, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69c021ca61688190875bd6107161c284 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:48 p.m.