Triple
T15721933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Westminster Under School |
E381115
|
entity |
| Predicate | hasSingleSexStatus |
P32136
|
FINISHED |
| Object | single-sex |
—
|
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: single-sex | Statement: [Westminster Under School, hasSingleSexStatus, single-sex]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSingleSexStatus Context triple: [Westminster Under School, hasSingleSexStatus, single-sex]
-
A.
isSingleSex
chosen
Indicates that the entity involves or is restricted to only one biological sex or gender, rather than being mixed or coeducational.
-
B.
hasSexStatus
Indicates that one entity has a particular sexual status or condition in relation to another entity or context.
-
C.
sexStatus
Indicates whether and how a sexual relationship or sexual activity exists or has occurred between the related entities.
-
D.
hasSex
Indicates that one entity engages in sexual activity with another entity.
-
E.
hasNumberOfGenders
Indicates the relationship that specifies how many distinct genders are associated with or recognized for a given entity.
- 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_69d86d9bf930819082b30cf6d169297c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04fb0b51081908e652ec4992296fa |
completed | April 16, 2026, 2:55 a.m. |
| PD | Predicate disambiguation | batch_69e00526759c819088b80d85138b8974 |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:45 a.m.