Triple
T2669458
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Law French |
E55713
|
entity |
| Predicate | largelyReplacedBy |
P101
|
FINISHED |
| Object | English in legal proceedings |
—
|
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: English in legal proceedings | Statement: [Law French, largelyReplacedBy, English in legal proceedings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: largelyReplacedBy Context triple: [Law French, largelyReplacedBy, English in legal proceedings]
-
A.
partlyReplacedBy
Indicates that one entity has been superseded or substituted in part, but not entirely, by another entity.
-
B.
placedBy
Indicates that one entity was positioned, set, or put in a location or context by another entity.
-
C.
usedInsteadOf
Indicates that one entity is employed or chosen as a substitute or replacement for another entity.
-
D.
wasSupersededBy
chosen
Indicates that one entity has been replaced or made obsolete by another entity that takes over its role or function.
-
E.
replacedSystemUsedUntil
Indicates that one system was used up until it was replaced by another system.
- 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.