Triple
T23886961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eaglesham |
E600360
|
entity |
| Predicate | layoutPeriod |
P153944
|
FINISHED |
| Object | 18th century |
—
|
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: 18th century | Statement: [Eaglesham, layoutPeriod, 18th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: layoutPeriod Context triple: [Eaglesham, layoutPeriod, 18th century]
-
A.
locationPeriod
Indicates that an entity is associated with being at a particular location during a specified time period.
-
B.
settingPeriodDuration
Indicates the length of time for which a particular setting or configuration remains in effect.
-
C.
displacementPeriod
Indicates the time interval over which an entity is moved or shifted from one position or state to another.
-
D.
mainSettingPeriod
Indicates the historical or temporal period in which the primary setting of a work or event takes place.
-
E.
periodizedAs
Indicates that something has been divided or organized into distinct time periods according to a particular periodization scheme.
- F. None of above. chosen
Provenance (4 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_69e295318e148190b9979d8fc02e168f |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1cd00dc8c8190af641147b2efff3e |
completed | April 29, 2026, 9:18 a.m. |
| PD | Predicate disambiguation | batch_69f1614e24b48190a1c8fb5b7c75ee0f |
completed | April 29, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f167dca3608190ace9d2eef56b2af6 |
completed | April 29, 2026, 2:07 a.m. |
Created at: April 17, 2026, 8:24 p.m.