Triple
T11247260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Max Steel (video game) |
E266237
|
entity |
| Predicate | hasEnemyType |
P15619
|
FINISHED |
| Object | supervillains |
—
|
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: supervillains | Statement: [Max Steel (video game), hasEnemyType, supervillains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEnemyType Context triple: [Max Steel (video game), hasEnemyType, supervillains]
-
A.
hasOpposingForceType
Indicates that one force is characterized as being of a type that opposes or counteracts another force.
-
B.
enemyType
chosen
Indicates that one entity is classified as an enemy of a specified type or category in relation to another entity.
-
C.
hasObstacleType
Indicates that an entity is associated with or characterized by a specific type or category of obstacle.
-
D.
hasOpposingFront
Indicates that one entity’s front side is directly facing or oriented opposite to the front side of another entity.
-
E.
hasOpposingSide
Indicates that one entity possesses or is associated with another entity that lies on the opposite or facing side relative to a reference orientation or boundary.
- 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_69d6aac7953c8190b82caf9d7640fdf9 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e91d1484819098ee6b2efb5316a5 |
completed | April 9, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69d7878906f48190b63ddc103a0c8f9b |
completed | April 9, 2026, 11:03 a.m. |
Created at: April 8, 2026, 9:31 p.m.