Triple
T8239021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siege of Przemyśl |
E192483
|
entity |
| Predicate | civilianPopulationInside |
P3412
|
FINISHED |
| Object | tens of thousands of civilians |
—
|
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: tens of thousands of civilians | Statement: [Siege of Przemyśl, civilianPopulationInside, tens of thousands of civilians]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: civilianPopulationInside Context triple: [Siege of Przemyśl, civilianPopulationInside, tens of thousands of civilians]
-
A.
humanSettlementInside
Indicates that one human settlement is located entirely within the geographic boundaries of another area or settlement.
-
B.
permanentPopulation
Indicates that an entity has a stable, long-term resident population rather than a temporary or transient presence.
-
C.
hasResidentPopulation
Indicates that a place or administrative area has a population of people who live there permanently or for an extended period.
-
D.
populationIncludes
Indicates that a population contains or encompasses the specified individual(s) or subgroup(s) as members or elements.
-
E.
hasPopulationApproximate
chosen
Indicates that an entity has an estimated or approximate population size, rather than an exact count.
- 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_69ca82dc8f148190a2c75a98501a7b91 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb783a8cf48190bf85394fd3bd79e2 |
completed | March 31, 2026, 7:31 a.m. |
| PD | Predicate disambiguation | batch_69cb36b1dea0819091418072501e79c1 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:47 p.m.