Triple
T13516780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Sydney Girls High School |
E322779
|
entity |
| Predicate | servesYears |
P110074
|
FINISHED |
| Object | secondary school years |
—
|
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: secondary school years | Statement: [North Sydney Girls High School, servesYears, secondary school years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesYears Context triple: [North Sydney Girls High School, servesYears, secondary school years]
-
A.
serviceYears
Indicates the number of years an entity has provided service or been in a particular role, position, or organization.
-
B.
appliesInYears
Indicates that something (such as a rule, condition, or effect) is valid, relevant, or in force during specific years.
-
C.
durationInYears
Indicates the length of time associated with something, measured in whole or fractional years.
-
D.
coversYearsTo
Indicates a temporal relationship where one entity spans, includes, or extends up to a specified year or range of years represented by the other entity.
-
E.
type1Years
Indicates the number of years associated with being in or under a specified "type1" classification or status.
- 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_69d80766a21881909f21a1b7421d3b8a |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafa0ed508190b2855171b1945e84 |
completed | April 12, 2026, 2:43 p.m. |
| PD | Predicate disambiguation | batch_69dbae0b63748190b5e207f84b2532ea |
completed | April 12, 2026, 2:36 p.m. |
| PDg | Predicate description generation | batch_69dbaee128d88190b097be17fdd2f92b |
completed | April 12, 2026, 2:40 p.m. |
Created at: April 9, 2026, 9:44 p.m.