Triple
T4383858
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lafayette, California |
E99192
|
entity |
| Predicate | hasHousingCharacteristic |
P40076
|
FINISHED |
| Object | predominantly single-family homes |
—
|
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: predominantly single-family homes | Statement: [Lafayette, California, hasHousingCharacteristic, predominantly single-family homes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHousingCharacteristic Context triple: [Lafayette, California, hasHousingCharacteristic, predominantly single-family homes]
-
A.
hasHousingAccess
Indicates that an entity has the ability, right, or opportunity to obtain or use suitable housing.
-
B.
hasHouse
Indicates that one entity possesses, owns, or is provided with a house in relation to another entity.
-
C.
hasHousingUnits
Indicates that an entity possesses or contains a specified number or set of housing units.
-
D.
housingPattern
chosen
Indicates the typical arrangement or distribution of housing units or residential structures within a given area or context.
-
E.
hasHouses
Indicates that one entity possesses, controls, or contains one or more houses in relation to another entity or context.
- 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_69b3454f739481909ff6c28331f0c0b9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35263970c8190904ee20d81715833 |
completed | March 12, 2026, 11:55 p.m. |
| PD | Predicate disambiguation | batch_69b34f557fe8819085032bf7f0cea5dc |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:18 p.m.