Triple
T26193004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern Tennessee |
E655017
|
entity |
| Predicate | hasTypicalSettlementSize |
P179001
|
FINISHED |
| Object | small city |
—
|
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: small city | Statement: [Southern Tennessee, hasTypicalSettlementSize, small city]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalSettlementSize Context triple: [Southern Tennessee, hasTypicalSettlementSize, small city]
-
A.
hasTypicalMemberSize
Indicates the usual or characteristic size associated with members of a given class or group.
-
B.
typicalSettlement
Indicates that the subject is a common or characteristic type of settlement typically found in the context of the object.
-
C.
hasHumanSettlement
Indicates that a location or area contains or is the site of a human settlement, such as a town, village, or city.
-
D.
isSparselySettled
Indicates that a place has a low population density, with inhabitants spread out over a large area rather than concentrated.
-
E.
isSettlement
Indicates that the subject entity functions as a human-inhabited place or community, such as a town, village, or city.
- 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_69ee5b48236c81908fe385b6afc4f60b |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f719cc31ec819099bebcf833b14d76 |
completed | May 3, 2026, 9:47 a.m. |
| PD | Predicate disambiguation | batch_69f71820c6c88190ab38b4fa626d22cc |
completed | May 3, 2026, 9:40 a.m. |
| PDg | Predicate description generation | batch_69f71995853c8190912025c0e83640c8 |
completed | May 3, 2026, 9:47 a.m. |
Created at: April 26, 2026, 8:45 p.m.