Triple
T4995915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siege of Riga (1700) |
E112244
|
entity |
| Predicate | garrisonStrengthApprox |
P13142
|
FINISHED |
| Object | about 4,000–5,000 Swedish troops |
—
|
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 4,000–5,000 Swedish troops | Statement: [Siege of Riga (1700), garrisonStrengthApprox, about 4,000–5,000 Swedish troops]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: garrisonStrengthApprox Context triple: [Siege of Riga (1700), garrisonStrengthApprox, about 4,000–5,000 Swedish troops]
-
A.
garrisonSize
chosen
Indicates the number of troops or defenders stationed at a particular location as its garrison.
-
B.
garrisonTown
Indicates that a town serves as a military base or station where armed forces are permanently or regularly housed.
-
C.
garrisonedForce
Indicates that a military force is stationed in and occupies a specific location, typically for defense or control.
-
D.
garrisonType
Indicates the specific kind or classification of military garrison associated with an entity.
-
E.
garrisonDuringWar
Indicates that a military force is stationed in a specific location for defense or control during a time of war.
- 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_69bd4432b32c81909f3b3c6bd10f0653 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7472a1dc8190942f568a81fdd961 |
completed | March 20, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69bd714aee2481908fb0dd5fa2daf3a1 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:34 p.m.