Triple
T2592493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cuban Espiritismo |
E58152
|
entity |
| Predicate | typeOfMediumship |
P40064
|
FINISHED |
| Object | trance mediumship |
—
|
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: trance mediumship | Statement: [Cuban Espiritismo, typeOfMediumship, trance mediumship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfMediumship Context triple: [Cuban Espiritismo, typeOfMediumship, trance mediumship]
-
A.
craftType
Indicates the specific kind or category of craft or vessel associated with an entity.
-
B.
hullType
Indicates the specific structural design or configuration of an object's hull, typically classifying how its outer body or shell is shaped or constructed.
-
C.
hasVesselType
Indicates that an entity is associated with or classified by a specific type of vessel (e.g., ship, boat, or container).
-
D.
shipTypeInvolved
Indicates that a particular type or class of ship is involved or participates in a specified event, situation, or relationship.
-
E.
tonnageClass
Indicates a classification relationship where an entity is assigned to a category based on its tonnage (weight or carrying capacity range).
- 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_69ab4ac019c8819094add11c46706e32 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd425851c819088db89713c07056f |
completed | March 7, 2026, 7:30 a.m. |
| PD | Predicate disambiguation | batch_69abd0d344988190a18dd93b13e002e6 |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd2baee308190bdaa41ef1f6bc9cc |
completed | March 7, 2026, 7:24 a.m. |
Created at: March 6, 2026, 9:49 p.m.