Triple
T13912728
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lady Thiang |
E334538
|
entity |
| Predicate | familyRoleInFiction |
P34570
|
FINISHED |
| Object | mother of Prince Chulalongkorn |
—
|
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: mother of Prince Chulalongkorn | Statement: [Lady Thiang, familyRoleInFiction, mother of Prince Chulalongkorn]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: familyRoleInFiction Context triple: [Lady Thiang, familyRoleInFiction, mother of Prince Chulalongkorn]
-
A.
fictionalRelationship
chosen
Indicates a relationship that exists only within a fictional or imagined context between entities.
-
B.
fictionalUniverseRole
Indicates the role or function an entity has within a particular fictional universe or narrative setting.
-
C.
roleInStories
Indicates the specific function, position, or character part an entity plays within one or more stories.
-
D.
narrativeRoleInSeries
Indicates the specific narrative function or role an entity plays within a particular series or serialized work.
-
E.
hasFictionalFamily
Indicates that an entity is associated with a family that exists only within a fictional or imaginary context.
- 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_69d81c5eaa9c819083b1ff8689179565 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de27245c648190b2946845ce0fdbf8 |
completed | April 14, 2026, 11:38 a.m. |
| PD | Predicate disambiguation | batch_69de059e4ba881908554f72e889719fa |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:16 p.m.