Triple
T31207566
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coriantumr |
E795642
|
entity |
| Predicate | survivedBattleCount |
P105747
|
FINISHED |
| Object | many great and terrible battles |
—
|
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: many great and terrible battles | Statement: [Coriantumr, survivedBattleCount, many great and terrible battles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: survivedBattleCount Context triple: [Coriantumr, survivedBattleCount, many great and terrible battles]
-
A.
battledIn
Indicates that two or more entities engaged in a battle or conflict that took place at a specific location or during a particular event.
-
B.
numberOfMajorBattles
chosen
Indicates the total count of significant or major battles associated with an entity or event.
-
C.
numberOfBattleshipsCompleted
Indicates the total count of battleships that have been fully constructed or completed.
-
D.
survivedConflict
Indicates that an entity continued to live or exist after experiencing and enduring a specific conflict or violent event.
-
E.
numberLaunchedInCombat
Indicates the quantity of times an entity has been launched or deployed specifically in combat operations.
- 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_69f224d8c6608190b7882466521f62be |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69c24de048190973b05290ff5c404 |
completed | May 3, 2026, 12:51 a.m. |
| PD | Predicate disambiguation | batch_69f696673214819094350e1d2648ef34 |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 29, 2026, 9:09 p.m.