Triple
T7892780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wellfield Academy |
E183274
|
entity |
| Predicate | hasGenderIntake |
P16158
|
FINISHED |
| Object | mixed |
—
|
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: mixed | Statement: [Wellfield Academy, hasGenderIntake, mixed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenderIntake Context triple: [Wellfield Academy, hasGenderIntake, mixed]
-
A.
admissionGender
chosen
Indicates the gender-based criteria or classification applied in the context of admission or entry decisions.
-
B.
hasGenderRequirement
Indicates that a particular role, activity, or context specifies a required or restricted gender for participation or eligibility.
-
C.
hasGenderFocus
Indicates that something is specifically concerned with, oriented toward, or primarily addressing a particular gender or gender-related issues.
-
D.
hasGenderSystem
Indicates that an entity employs or is characterized by a particular system for categorizing gender.
-
E.
hasGenderInterpretation
Indicates that an entity is associated with a particular interpretation or understanding of gender.
- 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_69ca828c474c8190a254d6499871eaff |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a008fb88190a039fec40483ab93 |
completed | March 31, 2026, 3:05 a.m. |
| PD | Predicate disambiguation | batch_69cae92b0cd881908e715a10d3252e83 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5 p.m.