Triple
T2799344
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bungalow Heaven |
E53113
|
entity |
| Predicate | lotPattern |
P8034
|
FINISHED |
| Object | regular rectangular residential 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: regular rectangular residential lots | Statement: [Bungalow Heaven, lotPattern, regular rectangular residential lots]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lotPattern Context triple: [Bungalow Heaven, lotPattern, regular rectangular residential lots]
-
A.
kitPattern
Indicates the design or visual pattern featured on a team's kit or uniform.
-
B.
locationPattern
Indicates a recurring or structured spatial relationship, where an entity consistently appears or is arranged in a particular type of location or spatial configuration.
-
C.
hatPattern
Indicates that one entity has a hat characterized by a specific pattern or design.
-
D.
pattern
chosen
Indicates that one entity exhibits, follows, or is characterized by a particular recurring form, structure, or arrangement associated with another entity.
-
E.
trackPattern
Indicates that one entity follows, monitors, or records the behavior or state of another according to a defined pattern or sequence.
- 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_69ab495a90788190941b6917e1eca3a6 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abddf31eec8190a898713e53d1aa5c |
completed | March 7, 2026, 8:12 a.m. |
| PD | Predicate disambiguation | batch_69abdd040f9481908e9c7a2df88ea1ae |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:58 p.m.