Triple
T511740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Habeas Corpus Act 1679 |
E10623
|
entity |
| Predicate | aimedAtProtecting |
P9207
|
FINISHED |
| Object | liberty of the subject |
—
|
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: liberty of the subject | Statement: [Habeas Corpus Act 1679, aimedAtProtecting, liberty of the subject]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aimedAtProtecting Context triple: [Habeas Corpus Act 1679, aimedAtProtecting, liberty of the subject]
-
A.
aimsToProtect
chosen
Indicates an intention or purpose to safeguard or defend one entity, value, or condition from harm, risk, or undesirable outcomes.
-
B.
protectionObjective
Indicates that one entity has the goal or purpose of safeguarding, defending, or preserving another entity or its interests.
-
C.
protects
Indicates taking action to keep someone or something safe from harm, danger, or negative effects.
-
D.
protectedBy
Indicates that one entity provides protection, defense, or safeguarding for another entity.
-
E.
defends
Indicates that one entity protects or supports another entity against attack, criticism, or harm.
- 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_69a2e84a0d08819087e01863fcd9abf1 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f16768c081909d05537ff070868b |
completed | Feb. 28, 2026, 1:45 p.m. |
| PD | Predicate disambiguation | batch_69a2edff001c81909182a7e26c6dc51b |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.