Triple
T19559399
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Double Oak, Texas |
E489401
|
entity |
| Predicate | landCharacteristic |
P86936
|
FINISHED |
| Object | predominantly single-family homes on large lots |
—
|
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 on large lots | Statement: [Double Oak, Texas, landCharacteristic, predominantly single-family homes on large lots]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: landCharacteristic Context triple: [Double Oak, Texas, landCharacteristic, predominantly single-family homes on large lots]
-
A.
estateCharacteristic
Indicates that an estate possesses a particular attribute, quality, or defining feature.
-
B.
landAreaCharacteristic
chosen
Indicates a relationship where a land area possesses a particular attribute, quality, or characteristic.
-
C.
landVariant
Indicates that one landform, terrain type, or land-related entity is an alternative or variant form of another.
-
D.
Land
Indicates that an entity arrives onto and comes to rest on a surface or ground, typically from the air or another elevated position.
-
E.
lakeProperty
Indicates that a property is located on, adjacent to, or otherwise directly associated with a lake.
- 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_69d8e8dc5d8c8190a6d7bd8864f43ca0 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63f731ae48190ade295c15db7f8ed |
completed | April 20, 2026, 3 p.m. |
| PD | Predicate disambiguation | batch_69e514d4df3c8190b7e9b3b4fdf9452a |
completed | April 19, 2026, 5:45 p.m. |
Created at: April 10, 2026, 1:42 p.m.