Triple
T2563768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lambeth 1930 Resolution on contraception |
E57301
|
entity |
| Predicate | languageCharacter |
P24616
|
FINISHED |
| Object | cautious |
—
|
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: cautious | Statement: [Lambeth 1930 Resolution on contraception, languageCharacter, cautious]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageCharacter Context triple: [Lambeth 1930 Resolution on contraception, languageCharacter, cautious]
-
A.
legalCharacter
Indicates that an entity possesses a status, role, or nature that is recognized and defined by law.
-
B.
regionCharacter
Indicates a characteristic, feature, or quality that typifies or defines a particular region.
-
C.
languageCharacterizedBy
chosen
Indicates that a language is defined or distinguished by a particular feature, property, or characteristic.
-
D.
languageOfLetters
Indicates that one entity is the language in which the other entity’s letters or written correspondence are composed.
-
E.
characterSetName
Indicates the name assigned to a particular character set used for encoding or representing characters.
- 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_69ab4a4ef9008190a0e6d4422b9418b7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd35c6ee88190b6eaa1841d3e99a4 |
completed | March 7, 2026, 7:27 a.m. |
| PD | Predicate disambiguation | batch_69abd0cc8d308190ae7aa32b8f5ae2e5 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:48 p.m.