Triple
T9596766
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caswell |
E231548
|
entity |
| Predicate | bearerCountRegion |
P89130
|
FINISHED |
| Object | English-speaking countries |
—
|
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-speaking countries | Statement: [Caswell, bearerCountRegion, English-speaking countries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bearerCountRegion Context triple: [Caswell, bearerCountRegion, English-speaking countries]
-
A.
numberOfRegions
Indicates the total count of distinct regions associated with or contained within a given entity.
-
B.
regionSeatsCount
Indicates the number of seats allocated or available within a specific region.
-
C.
hasRegionStrongPresence
Indicates that an entity maintains a significant, influential, or concentrated presence within a specified region.
-
D.
ayahCount
Indicates the number of verses (ayahs) associated with a given surah or Quranic unit.
-
E.
hasRegion
Indicates that an entity includes, contains, or is associated with a specific geographic or administrative region as part of its scope or structure.
- 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_69ca8482884481908eccdfdf64d6fbf7 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9a34f5408190ba72ba8311eb259c |
completed | April 1, 2026, 10:20 p.m. |
| PD | Predicate disambiguation | batch_69ccd5a359788190b24f82399489f7fe |
completed | April 1, 2026, 8:21 a.m. |
| PDg | Predicate description generation | batch_69ccd93fc45c8190a823305e461e581d |
completed | April 1, 2026, 8:37 a.m. |
Created at: March 30, 2026, 8:07 p.m.