Triple
T36725850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eloise Turner |
E907193
|
entity |
| Predicate | timeSettingPrimary |
P123135
|
FINISHED |
| Object | contemporary 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: contemporary London | Statement: [Eloise Turner, timeSettingPrimary, contemporary London]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeSettingPrimary Context triple: [Eloise Turner, timeSettingPrimary, contemporary London]
-
A.
timeSettingVariant
Indicates a relationship where one time setting is an alternative or modified version of another time setting.
-
B.
timeOfSetting
Indicates the specific time at which an event, object, or phenomenon is set, scheduled, or takes place.
-
C.
timeProperty
Indicates that one entity specifies, constrains, or characterizes a temporal aspect or timing-related attribute of another entity.
-
D.
mainSettingPeriod
chosen
Indicates the historical or temporal period in which the primary setting of a work or event takes place.
-
E.
timeDesignation
Indicates that one entity assigns, specifies, or denotes a particular time or temporal label for another entity or event.
- 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_69f76e746e4c8190a0d05cc6d57a643e |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f9fd6834cc8190aa27153d6a99f3bb |
completed | May 5, 2026, 2:23 p.m. |
| PD | Predicate disambiguation | batch_69f7cf7890008190a8bc355ff2d61c86 |
completed | May 3, 2026, 10:43 p.m. |
Created at: May 3, 2026, 4:12 p.m.