Triple
T7002483
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | His Majesty the King (Thailand) |
E162369
|
entity |
| Predicate | genderImplication |
P73532
|
FINISHED |
| Object | male monarch |
—
|
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: male monarch | Statement: [His Majesty the King (Thailand), genderImplication, male monarch]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genderImplication Context triple: [His Majesty the King (Thailand), genderImplication, male monarch]
-
A.
genderSignificance
Indicates the relevance or impact that an entity’s gender has within a particular context, relationship, or interpretation.
-
B.
genderConfiguration
Indicates how the genders of the involved entities are arranged or combined within a particular relationship or context.
-
C.
genderUsage
Indicates how a particular gender is applied, referenced, or treated within a given context or system.
-
D.
genderDivision
Indicates a relationship where roles, responsibilities, or categories are separated or distinguished based on gender.
-
E.
genderRule
Indicates a rule or constraint that determines how gender-related properties or classifications should be assigned or interpreted in a given context.
- 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_69c68857ffc08190857dc62cd5253777 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dc1115c48190a9363473ae21b6c1 |
completed | March 27, 2026, 7:35 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c67c94819084fdcf0398606027 |
completed | March 27, 2026, 7:17 p.m. |
| PDg | Predicate description generation | batch_69c6d8c575f081908b43d95d1d99b1a4 |
completed | March 27, 2026, 7:21 p.m. |
Created at: March 27, 2026, 2:33 p.m.