Triple
T3537671
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luigi's Mansion |
E74806
|
entity |
| Predicate | featuresMechanic |
P48192
|
FINISHED |
| Object | ghost capturing |
—
|
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: ghost capturing | Statement: [Luigi's Mansion, featuresMechanic, ghost capturing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresMechanic Context triple: [Luigi's Mansion, featuresMechanic, ghost capturing]
-
A.
featuresVehicle
Indicates that one entity includes, presents, or prominently incorporates a particular vehicle as part of its content, composition, or offering.
-
B.
featuresSuit
Indicates that one entity includes or presents a particular suit (e.g., clothing, armor, or outfit) as a notable component or attribute.
-
C.
equipmentCharacteristic
Indicates that a specific characteristic, property, or attribute is associated with a piece of equipment.
-
D.
engineeringFeature
Indicates that one entity serves as an engineering-related feature, component, or characteristic of another entity within a technical or designed system.
-
E.
featuresCross
Indicates that one feature or element intersects or passes across another in space or structure.
- F. None of above. chosen
Provenance (4 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_69ad85d274cc8190ab59c97298a1cfbf |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbcc928248190b851f8280d58cfcf |
completed | March 8, 2026, 6:15 p.m. |
| PD | Predicate disambiguation | batch_69adae13ab808190a5d6ecdc7543445e |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adaed7f2ec819085467d281712e0e8 |
completed | March 8, 2026, 5:16 p.m. |
Created at: March 8, 2026, 3:20 p.m.