Triple
T37513486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Search for Cain |
E932572
|
entity |
| Predicate | involvesEnemyType |
P15619
|
FINISHED |
| Object | Fallen |
—
|
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: Fallen | Statement: [The Search for Cain, involvesEnemyType, Fallen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: involvesEnemyType Context triple: [The Search for Cain, involvesEnemyType, Fallen]
-
A.
enemyType
chosen
Indicates that one entity is classified as an enemy of a specified type or category in relation to another entity.
-
B.
enemyTypeOpposed
Indicates that one type of enemy is defined as being in opposition or conflict with another enemy type.
-
C.
hasEnemiesTrait
Indicates that an entity possesses a characteristic or quality specifically related to having enemies.
-
D.
enemyCharacterIn
Indicates that a character is located within or present inside an enemy-controlled area, zone, or context.
-
E.
involvesWeaponType
Indicates that the relationship or action includes the use, presence, or association of a specific type or category of weapon.
- 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_69f76ec730988190b5aa4f9cb9afd518 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fe9fb9735c8190a360b556c9d00b3f |
completed | May 9, 2026, 2:45 a.m. |
| PD | Predicate disambiguation | batch_69fe9eaa88008190a9b2a469dc685002 |
completed | May 9, 2026, 2:40 a.m. |
Created at: May 3, 2026, 4:17 p.m.