Triple
T34183875
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al-Azza |
E876901
|
entity |
| Predicate | hasCampLayout |
P199819
|
FINISHED |
| Object | narrow streets |
—
|
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: narrow streets | Statement: [Al-Azza, hasCampLayout, narrow streets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCampLayout Context triple: [Al-Azza, hasCampLayout, narrow streets]
-
A.
hasCampType
Indicates that an entity is associated with or classified by a particular type or category of camp.
-
B.
hasCourseLayout
Indicates that an entity is associated with, or defined by, a specific arrangement or structure of a course (such as its sequence, modules, or components).
-
C.
hasCampCode
Indicates that an entity is associated with a specific camp identifier or code.
-
D.
hasOutdoorLayout
Indicates that an entity includes, features, or is associated with a specific arrangement or design intended for an outdoor space.
-
E.
hasFloorLayout
Indicates that something is associated with or defined by a specific floor layout or arrangement of spaces on a floor.
- F. None of above. chosen
Provenance (4 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_69f349ae640c8190b9cd220b5368d8b6 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff59b33a38819086cc9aa19b81748b |
completed | May 9, 2026, 3:58 p.m. |
| PD | Predicate disambiguation | batch_69ff587758f88190a39c2164341dc554 |
completed | May 9, 2026, 3:53 p.m. |
| PDg | Predicate description generation | batch_69ff59b1e2ac8190bb65529e9dbbb178 |
completed | May 9, 2026, 3:58 p.m. |
Created at: May 1, 2026, 1:55 a.m.