Triple
T3646563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lisa |
E77314
|
entity |
| Predicate | temporalSettingOfWork |
P15236
|
FINISHED |
| Object | contemporary era |
—
|
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: contemporary era | Statement: [Lisa, temporalSettingOfWork, contemporary era]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: temporalSettingOfWork Context triple: [Lisa, temporalSettingOfWork, contemporary era]
-
A.
workSettingPeriod
Indicates the time period during which a particular work setting or employment context is in effect.
-
B.
workPeriod
Indicates the span of time during which an entity is engaged in a particular work or employment activity.
-
C.
settingOfWork
chosen
Indicates the place, time, or environment in which a creative work’s narrative or events are situated.
-
D.
temporalAspect
Indicates the time-related characteristics or phase (such as duration, frequency, or temporal status) associated with an event or relationship.
-
E.
timeOfSetting
Indicates the specific time at which an event, object, or phenomenon is set, scheduled, or takes place.
- 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_69ad85de1b988190a45f8dbfebc806fc |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc3895198819090a17a8894e91d00 |
completed | March 8, 2026, 6:44 p.m. |
| PD | Predicate disambiguation | batch_69adb8445b2c8190ab07f6ad4e010d0e |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:24 p.m.