Triple
T18119000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Modi'in-Maccabim-Re'ut |
E433683
|
entity |
| Predicate | hasPlannedUrbanDesign |
P92984
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Modi'in-Maccabim-Re'ut, hasPlannedUrbanDesign, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPlannedUrbanDesign Context triple: [Modi'in-Maccabim-Re'ut, hasPlannedUrbanDesign, true]
-
A.
hasUrbanPlanning
Indicates that an entity is involved in, responsible for, or characterized by activities or attributes related to urban planning.
-
B.
hasPlannedUrbanCharacter
Indicates that an area exhibits an intentionally designed and organized urban form, layout, and land use pattern rather than informal or unplanned development.
-
C.
hasUrbanDesign
chosen
Indicates that an entity possesses or is associated with a specific urban design plan, feature, or configuration.
-
D.
hasUrbanPlanner
Indicates that an entity is associated with or utilizes a specific urban planner responsible for planning or managing its urban development.
-
E.
hasUrbanDesignFocus
Indicates a relationship where an entity is concerned with, oriented toward, or specialized in urban design as a primary focus.
- 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_69d8b909e8cc81908df4cc2b8ea6d11f |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddd843e88190abbc173dbc9b450a |
completed | April 19, 2026, 1:51 p.m. |
| PD | Predicate disambiguation | batch_69e43313ca788190baa224269e71de49 |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:28 a.m.