Triple
T11331618
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pioneer Column expedition |
E268355
|
entity |
| Predicate | numberOfSettlers |
P78459
|
FINISHED |
| Object | about 200 |
—
|
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: about 200 | Statement: [Pioneer Column expedition, numberOfSettlers, about 200]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSettlers Context triple: [Pioneer Column expedition, numberOfSettlers, about 200]
-
A.
numberOfInitialSettlers
chosen
Indicates the quantity of settlers present at the initial establishment of a settlement or colony.
-
B.
numberOfSettlersCaptured
Indicates the quantity of settlers who have been taken captive in a given context or event.
-
C.
numberOfOriginalSettlerFamilies
Indicates the count of distinct families that were part of the initial group of settlers in a given place or community.
-
D.
settlerType
Indicates the specific category or classification of a settler involved in the relationship or context.
-
E.
settlerOf
Indicates that an entity established or inhabited a place as a settler of that location.
- 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_69d6aacb1f0881908c84a349fd1be047 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9fd38308190a5458be1bfcc89ea |
completed | April 9, 2026, 6:03 p.m. |
| PD | Predicate disambiguation | batch_69d787afe5a48190b8af1a3e19529641 |
completed | April 9, 2026, 11:04 a.m. |
Created at: April 8, 2026, 9:32 p.m.