Triple
T4295746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Leys School |
E99706
|
entity |
| Predicate | hasReligiousEthos |
P27703
|
FINISHED |
| Object | Christian |
—
|
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: Christian | Statement: [The Leys School, hasReligiousEthos, Christian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReligiousEthos Context triple: [The Leys School, hasReligiousEthos, Christian]
-
A.
hasReligiousTheme
Indicates that something (such as a work, event, or object) centrally involves or expresses religious ideas, symbols, practices, or narratives.
-
B.
hasReligiousCharacter
chosen
Indicates that an entity possesses a religious nature, function, or affiliation, or is characterized by religious aspects or significance.
-
C.
hasReligiousOrigin
Indicates that something originates from, is derived from, or is fundamentally based on a religious tradition, belief system, or practice.
-
D.
religiousAttitude
Indicates an entity’s stance, disposition, or orientation toward religion or religious beliefs.
-
E.
hasEthicalDimension
Indicates that the relationship, action, or situation involves moral considerations, value judgments, or ethical implications.
- 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_69b3455175088190aa79c6e03b86647e |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35085b864819086cf726285384566 |
completed | March 12, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_69b347fe55a88190b77bab0c0f38e1aa |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:08 p.m.