Triple
T34061373
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elsa Mars |
E873499
|
entity |
| Predicate | backstoryTimePeriod |
P167295
|
FINISHED |
| Object | 1930s |
—
|
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 | Statement: [Elsa Mars, backstoryTimePeriod, 1930s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: backstoryTimePeriod Context triple: [Elsa Mars, backstoryTimePeriod, 1930s]
-
A.
chronologicalBackstoryIn
chosen
Indicates that one event or narrative element serves as a prior backstory that occurs earlier in time within the timeline of another event or narrative.
-
B.
chroniclesPeriodFrom
Indicates that something documents or records events starting from a specified point in time or historical period.
-
C.
settingDepictedPeriod
Indicates the historical or temporal period in which the setting of something (e.g., a work or scene) is depicted.
-
D.
historicalIntroductionPeriod
Indicates the time period during which something was first introduced or came into use in a historical context.
-
E.
occupationPeriod
Indicates the time span during which an entity holds or held a particular occupation or role.
- 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_69f349a4af208190afa14888f9c9fb9d |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f70b9be10c819081f456a7b4f35d15 |
completed | May 3, 2026, 8:47 a.m. |
| PD | Predicate disambiguation | batch_69f70ac0170c819098e3b8e41d02efef |
completed | May 3, 2026, 8:43 a.m. |
Created at: May 1, 2026, 1:52 a.m.