Triple
T35700806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Derajat region |
E1031575
|
entity |
| Predicate | linguisticZoneOf |
P17400
|
FINISHED |
| Object | Saraiki–Punjabi transition |
—
|
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: Saraiki–Punjabi transition | Statement: [Derajat region, linguisticZoneOf, Saraiki–Punjabi transition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linguisticZoneOf Context triple: [Derajat region, linguisticZoneOf, Saraiki–Punjabi transition]
-
A.
linguisticArea
chosen
Indicates a regional context in which languages share features due to geographic proximity and contact rather than common genetic origin.
-
B.
linguisticStatusOfArea
Indicates the linguistic status or condition that characterizes a particular geographic area.
-
C.
languageZone
Indicates the linguistic region or area in which a language is predominantly used or officially recognized.
-
D.
languageArea
Indicates the geographic or cultural region in which a particular language is used or predominantly spoken.
-
E.
linguisticScope
Indicates the range or domain within language (such as a phrase, clause, or discourse segment) over which a particular linguistic element, feature, or operation has effect.
- 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_69f76e0d393c8190b6303c64408736db |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a34f8ee08190a040304635539a8f |
completed | May 3, 2026, 7:34 p.m. |
| PD | Predicate disambiguation | batch_69f7a06f125c8190843af194f042a465 |
completed | May 3, 2026, 7:22 p.m. |
Created at: May 3, 2026, 4:05 p.m.