Triple
T7411755
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Richton Park, Illinois |
E171020
|
entity |
| Predicate | hasLevelOfSettlement |
P70399
|
FINISHED |
| Object | suburban |
—
|
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: suburban | Statement: [Richton Park, Illinois, hasLevelOfSettlement, suburban]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLevelOfSettlement Context triple: [Richton Park, Illinois, hasLevelOfSettlement, suburban]
-
A.
isSettlementOf
Indicates that one entity is a settlement (such as a town, village, or city) that belongs to, is located within, or is administratively part of another entity.
-
B.
hasHumanSettlement
Indicates that a location or area contains or is the site of a human settlement, such as a town, village, or city.
-
C.
hasPortSettlement
Indicates that a place has a settlement located at or directly associated with a port for maritime or water-based transport.
-
D.
settlementState
Indicates the state or status of a settlement process or transaction at a given point in time.
-
E.
humanSettlementLevel
chosen
Indicates the degree or intensity of human settlement present in a given area, such as how densely or extensively it is inhabited or developed.
- 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_69c68a618bdc81908d8018edadecd1a4 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f2a027148190bdb6a7940389e377 |
completed | March 27, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69c6f0345040819094c5756dfa487faf |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:11 p.m.