Triple
T21495893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States (during Revolutionary War) |
E530351
|
entity |
| Predicate | hasNumberOfConstituentColonies |
P144623
|
FINISHED |
| Object | 13 |
—
|
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: 13 | Statement: [United States (during Revolutionary War), hasNumberOfConstituentColonies, 13]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfConstituentColonies Context triple: [United States (during Revolutionary War), hasNumberOfConstituentColonies, 13]
-
A.
hasNumberOfDependentTerritories
Indicates the quantitative relationship specifying how many dependent territories are associated with a given entity.
-
B.
hasOverseasTerritory
Indicates that one entity possesses or controls a territory located outside its own primary geographic or sovereign domain.
-
C.
hasSovereignState
Indicates that one entity is the sovereign state that has ultimate authority or jurisdiction over another entity.
-
D.
numberOfUnionTerritories
Indicates the total count of union territories associated with a given country or administrative entity.
-
E.
colonies
Indicates that one entity establishes or maintains a dependent settlement or territory in or on another 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_69e0c45bd15481909fba5910765cdda2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea582d9c8190b95ff6e1b8179b81 |
completed | April 23, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69e631f6e68081908f5ee4ce7413803e |
completed | April 20, 2026, 2:02 p.m. |
| PDg | Predicate description generation | batch_69e6386c5a4481909c37f7de7e9fc025 |
completed | April 20, 2026, 2:30 p.m. |
Created at: April 16, 2026, 6:23 p.m.