Triple
T9478249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BSL |
E228567
|
entity |
| Predicate | hasAcquisition |
P88341
|
FINISHED |
| Object | first language for many Deaf children in the UK |
—
|
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: first language for many Deaf children in the UK | Statement: [BSL, hasAcquisition, first language for many Deaf children in the UK]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAcquisition Context triple: [BSL, hasAcquisition, first language for many Deaf children in the UK]
-
A.
hasAcquisitionType
Indicates the specific kind or category of acquisition relationship that exists between one entity acquiring another.
-
B.
acquiredWith
Indicates that one entity was obtained, purchased, or gained together with or by means of another entity.
-
C.
acquisitionStatus
Indicates the current state or outcome of an acquisition process between entities (e.g., pending, completed, failed, or canceled).
-
D.
acquiredFor
Indicates that one entity obtained or purchased another entity specifically for the benefit, use, or purpose of a third entity.
-
E.
acquisitionResultedIn
Indicates that an acquisition event led to a particular outcome, state, or consequence for the involved entities.
- F. None of above. chosen
Provenance (4 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_69ca847162c48190b079076c9595513c |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd8014fd0c819093bd15816f3db357 |
completed | April 1, 2026, 8:29 p.m. |
| PD | Predicate disambiguation | batch_69cca55f01b081908dc0f12eaa45f832 |
completed | April 1, 2026, 4:55 a.m. |
| PDg | Predicate description generation | batch_69cca89d0f0c8190b4528990fe708fca |
completed | April 1, 2026, 5:09 a.m. |
Created at: March 30, 2026, 7:54 p.m.