Triple
T27211321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Little Ethiopia (Los Angeles) |
E684002
|
entity |
| Predicate | hasStreetSign |
P66816
|
FINISHED |
| Object | "Little Ethiopia" neighborhood sign |
—
|
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: "Little Ethiopia" neighborhood sign | Statement: [Little Ethiopia (Los Angeles), hasStreetSign, "Little Ethiopia" neighborhood sign]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStreetSign Context triple: [Little Ethiopia (Los Angeles), hasStreetSign, "Little Ethiopia" neighborhood sign]
-
A.
hasRoadSign
chosen
Indicates that one entity possesses, displays, or is associated with a particular road sign.
-
B.
hasStreet
Indicates that an entity is located on, associated with, or identified by a particular street.
-
C.
hasSignageName
Indicates that an entity has a specific name or label as it appears on its physical signage.
-
D.
hasSignageIn
Indicates that appropriate signs or signage for an entity are present or installed within a specified location or area.
-
E.
hasSignageLetter
Indicates that an object or location bears signage containing a specific letter or set of letters.
- 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_69fb3425666081908916fcbf3b5dd907 |
completed | May 6, 2026, 12:29 p.m. |
| PD | Predicate disambiguation | batch_69fb2f5f3164819099429c2cc3d24e01 |
completed | May 6, 2026, 12:09 p.m. |
Created at: April 27, 2026, 9:39 a.m.