Triple
T15586376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | His Majesty the King of Greece |
E374631
|
entity |
| Predicate | genderSpecificity |
P119314
|
FINISHED |
| Object | male |
—
|
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 | Statement: [His Majesty the King of Greece, genderSpecificity, male]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genderSpecificity Context triple: [His Majesty the King of Greece, genderSpecificity, male]
-
A.
genderUsage
Indicates how a particular gender is applied, referenced, or treated within a given context or system.
-
B.
genderSignificance
Indicates the relevance or impact that an entity’s gender has within a particular context, relationship, or interpretation.
-
C.
genderConfiguration
Indicates how the genders of the involved entities are arranged or combined within a particular relationship or context.
-
D.
genderCustom
Indicates that an entity has a user-specified or non-standard gender designation beyond predefined gender categories.
-
E.
genderTarget
Indicates that an action, message, or effect is specifically directed toward entities of a particular gender.
- 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_69d85ccd575081908909b71a3f3e3a61 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e4900408190aadb48b001db4169 |
completed | April 16, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69deda817e9881909b0c66fc9056f7d5 |
completed | April 15, 2026, 12:23 a.m. |
| PDg | Predicate description generation | batch_69dff7f05f708190850f1d8782e132b0 |
completed | April 15, 2026, 8:41 p.m. |
Created at: April 10, 2026, 4:11 a.m.