Triple
T32082027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shibpur Hindu Girls High School |
E819323
|
entity |
| Predicate | studentGenderFocus |
P2452
|
FINISHED |
| Object | female |
—
|
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: female | Statement: [Shibpur Hindu Girls High School, studentGenderFocus, female]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: studentGenderFocus Context triple: [Shibpur Hindu Girls High School, studentGenderFocus, female]
-
A.
hasGenderFocus
chosen
Indicates that something is specifically concerned with, oriented toward, or primarily addressing a particular gender or gender-related issues.
-
B.
genderRatio
Indicates the proportional relationship between different genders within a given group or population.
-
C.
featuredGender
Indicates that a particular gender is highlighted, emphasized, or given primary focus in a given context or presentation.
-
D.
admissionGender
Indicates the gender-based criteria or classification applied in the context of admission or entry decisions.
-
E.
hasPupilsGender
Indicates that an entity has pupils whose gender is specified or characterized in some way.
- 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_69f348ff8ef88190931c08ba530a36bc |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b580c3e481909f45d1716cde89ad |
completed | May 3, 2026, 2:40 a.m. |
| PD | Predicate disambiguation | batch_69f6b3a7bdb481908d16a32f49e38c2c |
completed | May 3, 2026, 2:32 a.m. |
Created at: May 1, 2026, 12:24 a.m.