Triple
T38130906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | רמת גן |
E952217
|
entity |
| Predicate | נמצאת באזור מטרופוליני |
P114292
|
FINISHED |
| Object | מטרופולין תל אביב |
—
|
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: מטרופולין תל אביב | Statement: [רמת גן, נמצאת באזור מטרופוליני, מטרופולין תל אביב]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: נמצאת באזור מטרופוליני Context triple: [רמת גן, נמצאת באזור מטרופוליני, מטרופולין תל אביב]
-
A.
locatedNearMetropolitanArea
Indicates that one entity is situated in close geographic proximity to a metropolitan (urban) area.
-
B.
operatesInMetropolitanArea
Indicates that an entity conducts its activities or provides its services within a specified metropolitan area.
-
C.
belongsToMetropolitanRegion
Indicates that one geographic or administrative area is part of, or included within, a larger metropolitan region.
-
D.
isMetropolitanArea
Indicates that a given area functions as a major urban center and its surrounding region, typically characterized by high population density and integrated economic and social activities.
-
E.
isWithinMetroArea
chosen
Indicates that one location lies inside the geographic boundaries of a specified metropolitan area.
- 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_69f76f083548819082bd2bbf53c79e8e |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fcd867f36081908c88c55a6a1404c1 |
completed | May 7, 2026, 6:22 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f47b188190b4cf4b4c748d9d03 |
completed | May 7, 2026, 5:55 p.m. |
Created at: May 3, 2026, 4:21 p.m.