Triple
T27162886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Four Courts, Dublin |
E682706
|
entity |
| Predicate | hasLawLibrary |
P46550
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Four Courts, Dublin, hasLawLibrary, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLawLibrary Context triple: [Four Courts, Dublin, hasLawLibrary, true]
-
A.
lawLibrary
chosen
Indicates a relationship where a location or resource functions as a library specifically dedicated to legal materials, services, or research.
-
B.
haveLaw
Indicates that a governing body or jurisdiction possesses, enforces, or is characterized by a particular law or set of laws.
-
C.
hasLawTheme
Indicates that something is related to, concerned with, or thematically focused on law or legal matters.
-
D.
majorLegalSource
Indicates that one entity serves as a primary or authoritative legal basis or reference for another entity.
-
E.
legalCodeFocus
Indicates that something is specifically concerned with, centered on, or primarily addressing a particular legal code or body of law.
- 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_69eefacf6e788190a75a64399d9e3109 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f7979a073881909a4fde2558e6b6f3 |
completed | May 3, 2026, 6:44 p.m. |
| PD | Predicate disambiguation | batch_69f7961550f88190b7bb8a9155458b54 |
completed | May 3, 2026, 6:38 p.m. |
Created at: April 27, 2026, 9:19 a.m.