Triple
T913767
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bourbon Reforms |
E19722
|
entity |
| Predicate | hasTemporalLocation |
P22881
|
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: [Bourbon Reforms, hasTemporalLocation, 18th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTemporalLocation Context triple: [Bourbon Reforms, hasTemporalLocation, 18th century]
-
A.
temporalRelation
Indicates a relationship that specifies how two events or states are positioned relative to each other in time (e.g., before, after, or overlapping).
-
B.
locatedInTimeZone
Indicates that an entity exists or an event occurs within the temporal bounds defined by a specific time zone.
-
C.
hasRelativeLocation
Indicates that one entity is positioned in space in relation to another entity’s location.
-
D.
currentLocationSince
Indicates the point in time since which an entity has been at its current location.
-
E.
timeCoordinateType
Indicates the specific temporal reference system or framework used to define and interpret time coordinates for an event or entity.
- 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_69a4939f91a08190ba68c2c81eab90fe |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b6755c488190b7f7848110e3ea2c |
completed | March 1, 2026, 9:58 p.m. |
| PD | Predicate disambiguation | batch_69a4b292d3408190947cbc2f794cf8c5 |
completed | March 1, 2026, 9:41 p.m. |
| PDg | Predicate description generation | batch_69a4b67499708190a65f24d1fd7e4ec5 |
completed | March 1, 2026, 9:58 p.m. |
Created at: March 1, 2026, 7:39 p.m.