Triple
T2469187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taipale |
E55328
|
entity |
| Predicate | resultOfBattles |
P19109
|
FINISHED |
| Object | heavy casualties on both sides |
—
|
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: heavy casualties on both sides | Statement: [Taipale, resultOfBattles, heavy casualties on both sides]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: resultOfBattles Context triple: [Taipale, resultOfBattles, heavy casualties on both sides]
-
A.
resultOfBattle
chosen
Indicates that one entity is the outcome or consequence produced by a specific battle or combat event involving another entity.
-
B.
battleOccurred
Indicates that a conflict or combat event took place between specified parties at a particular time and/or location.
-
C.
battleOccurredOn
Indicates that a specific battle took place at or on a particular location or date.
-
D.
battleAlsoKnownAs
Indicates that a particular battle is known by an alternative name or names.
-
E.
battleOccurredNear
Indicates that a battle took place in spatial proximity to a specified location or entity.
- 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_69ab49e3622c8190ad22afa2c4fbb807 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd2bc7b5481908b3664495e99f1a4 |
completed | March 7, 2026, 7:24 a.m. |
| PD | Predicate disambiguation | batch_69abd0b3ea308190a6d8499c2a542c50 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:44 p.m.