Triple
T27782582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lyon Estates |
E699371
|
entity |
| Predicate | fictionalAddressOfMainHouse |
P14481
|
FINISHED |
| Object | 9303 Lyon Drive |
—
|
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: 9303 Lyon Drive | Statement: [Lyon Estates, fictionalAddressOfMainHouse, 9303 Lyon Drive]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalAddressOfMainHouse Context triple: [Lyon Estates, fictionalAddressOfMainHouse, 9303 Lyon Drive]
-
A.
fictionalAddress
chosen
Indicates that an address associated with an entity is invented or not corresponding to a real-world location.
-
B.
fictionalResidence
Indicates that one entity is the place where another entity lives or is based within a fictional or imaginary context.
-
C.
hasFictionalHouseNumberRange
Indicates that an entity is associated with a range of house numbers that are fictional or not used in real-world addressing.
-
D.
streetAddress
Indicates the specific location of an entity in terms of its numbered building and street name within a postal address.
-
E.
hasFictionalAddressTown
Indicates that an entity is associated with a town that serves as its fictional address location.
- 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_69ef6a4b5a9081909c9111396c2be3d2 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f7117e55908190a67105e92bc4830f |
completed | May 3, 2026, 9:12 a.m. |
| PD | Predicate disambiguation | batch_69f70f380690819090cc34763ba460ed |
completed | May 3, 2026, 9:02 a.m. |
Created at: April 27, 2026, 5:11 p.m.