Triple
T27211405
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ethiopian community in Los Angeles |
E684004
|
entity |
| Predicate | hasNeighborhoodConcentration |
P70368
|
FINISHED |
| Object | Pico Boulevard corridor |
—
|
NE NERFINISHED |
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: Pico Boulevard corridor | Statement: [Ethiopian community in Los Angeles, hasNeighborhoodConcentration, Pico Boulevard corridor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNeighborhoodConcentration Context triple: [Ethiopian community in Los Angeles, hasNeighborhoodConcentration, Pico Boulevard corridor]
-
A.
hasNeighbourhood
Indicates that one entity is located within, or is associated with, a particular neighborhood area of another entity.
-
B.
hasNeighbourhoodCount
Indicates the number of neighbourhoods associated with a given entity.
-
C.
hasCoordinateConcentration
Indicates that an entity has a specific concentration value associated with a particular spatial or coordinate location.
-
D.
hasPopulationConcentrationIn
chosen
Indicates that a population is densely or significantly clustered within a specified geographic area or region.
-
E.
hasNeighbourhoodStatus
Indicates that an entity has a particular status, classification, or condition specifically in relation to a given neighbourhood.
- 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_69eefad339a08190aeacb2a198f1a39b |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69fbbc49da8c8190902bbb05d2477cab |
completed | May 6, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69fbb13f34b08190bbbb220ac1e6e666 |
completed | May 6, 2026, 9:23 p.m. |
Created at: April 27, 2026, 9:39 a.m.