Triple
T19339131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Briggs Plan |
E483702
|
entity |
| Predicate | numberOfNewVillagesCreated |
P73102
|
FINISHED |
| Object | over 400 |
—
|
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: over 400 | Statement: [Briggs Plan, numberOfNewVillagesCreated, over 400]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfNewVillagesCreated Context triple: [Briggs Plan, numberOfNewVillagesCreated, over 400]
-
A.
numberOfVillages
chosen
Indicates the count of villages associated with a given entity or within a specified area or context.
-
B.
numberOfDestroyedVillages
Indicates the count of villages that have been destroyed in the context of the described situation or event.
-
C.
numberOfNewRegions
Indicates the count of regions that have been newly created or added within a specified context or time frame.
-
D.
hasLargestVillage
Indicates that one entity possesses or contains the village that is largest in size or population within a specified context or set.
-
E.
numberOfInitialSettlers
Indicates the quantity of settlers present at the initial establishment of a settlement or colony.
- 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_69d8e8d244f8819080eb1f3491300db2 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e618560f0081908565f802ea1e3cc8 |
completed | April 20, 2026, 12:13 p.m. |
| PD | Predicate disambiguation | batch_69e4dd12303c8190a2027c062b2dff40 |
completed | April 19, 2026, 1:48 p.m. |
Created at: April 10, 2026, 1:33 p.m.