Triple
T27829975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamburg Township, Michigan |
E703065
|
entity |
| Predicate | hasResidentialDevelopmentPattern |
P40076
|
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: [Hamburg Township, Michigan, hasResidentialDevelopmentPattern, suburban]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasResidentialDevelopmentPattern Context triple: [Hamburg Township, Michigan, hasResidentialDevelopmentPattern, suburban]
-
A.
hasDevelopingResidentialZones
Indicates that an area or region contains residential zones that are currently under development or in the process of being built.
-
B.
hasResidentialBuilding
Indicates that an entity possesses, contains, or is associated with a residential building as part of its properties or components.
-
C.
hasResidentialBuildingsType
Indicates that an entity is associated with a specific type or category of residential buildings.
-
D.
housingPattern
chosen
Indicates the typical arrangement or distribution of housing units or residential structures within a given area or context.
-
E.
hasResidentialArea
Indicates that an entity includes, contains, or is associated with an area designated for people to live or reside.
- 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_69ef840b94b08190950a4f77296938b2 |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69ff0e9c75208190a4423261f00b79b3 |
completed | May 9, 2026, 10:38 a.m. |
| PD | Predicate disambiguation | batch_69ff0e07f08481909c4ae322632a6bf0 |
completed | May 9, 2026, 10:35 a.m. |
Created at: April 27, 2026, 5:55 p.m.