Triple
T2489430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King George Street, Jerusalem |
E52003
|
entity |
| Predicate | hasStreetLighting |
P1280
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [King George Street, Jerusalem, hasStreetLighting, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStreetLighting Context triple: [King George Street, Jerusalem, hasStreetLighting, yes]
-
A.
hasLighting
chosen
Indicates that one entity is equipped with, contains, or is characterized by a particular type or configuration of lighting.
-
B.
numberOfLights
Indicates the quantity of lights associated with or present on a given entity.
-
C.
hasRunwayLighting
Indicates that a runway is equipped with lighting systems to aid visibility and operations, typically during low-light or night conditions.
-
D.
isIlluminatedAtNight
Indicates that an entity receives or emits sufficient light to be visibly illuminated during nighttime conditions.
-
E.
hasTreeLinedStreets
Indicates that the streets in a given area are lined or bordered with trees along their sides.
- 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_69ab4955111c8190835bf619adec21ff |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd20b6d008190acec0eb172e218c9 |
completed | March 7, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69abd0b7cf088190bcff4dac6150044c |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:45 p.m.