Triple
T2669460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Law French |
E55713
|
entity |
| Predicate | remainsInUseAs |
P27206
|
FINISHED |
| Object | source of traditional legal terms |
—
|
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: source of traditional legal terms | Statement: [Law French, remainsInUseAs, source of traditional legal terms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: remainsInUseAs Context triple: [Law French, remainsInUseAs, source of traditional legal terms]
-
A.
stillUsedBy
chosen
Indicates that something continues to be used or relied upon by another entity at the present time.
-
B.
isUsedAs
Indicates that one entity serves a particular function, role, or purpose as another entity.
-
C.
isInUse
Indicates that an entity is currently being utilized or actively engaged in its intended function or operation.
-
D.
areUsedIn
Indicates that certain entities serve as components, tools, or resources within a particular process, context, or application.
-
E.
hasRemainsOf
Indicates that one entity physically contains, preserves, or is associated with the leftover physical traces or remnants of another entity.
- 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_69ab49e54de48190be708cd1cf8be073 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd98d32ac8190b8edd9421b706532 |
completed | March 7, 2026, 7:53 a.m. |
| PD | Predicate disambiguation | batch_69abd8190ad481908f3e14ac84d0940a |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:54 p.m.