Triple
T71404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sunset Boulevard |
E1428
|
entity |
| Predicate | hasSectionCharacter |
P274
|
FINISHED |
| Object | commercial areas |
—
|
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: commercial areas | Statement: [Sunset Boulevard, hasSectionCharacter, commercial areas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSectionCharacter Context triple: [Sunset Boulevard, hasSectionCharacter, commercial areas]
-
A.
hasSpecialCharacter
Indicates that a given entity (such as a string or identifier) contains at least one non-alphanumeric special character.
-
B.
hasSectionCount
Indicates that an entity is associated with a specific number of sections it contains or comprises.
-
C.
hasSegmentType
Indicates that an entity is associated with, or classified by, a particular type or category of segment within a larger structure or sequence.
-
D.
hasSectionKnownAs
Indicates that an entity includes a section or part that is referred to by a specific name.
-
E.
hasCharacteristic
chosen
Indicates that an entity possesses, exhibits, or is defined by a particular attribute, feature, or quality.
- 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_69a24c06b3bc8190aa4ac89026115efc |
completed | Feb. 28, 2026, 1:59 a.m. |
| NER | Named-entity recognition | batch_69a24f6997c081908b202f937eb2b14f |
completed | Feb. 28, 2026, 2:14 a.m. |
| PD | Predicate disambiguation | batch_69a24eab7f408190a8275cb82474f575 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:03 a.m.