Triple
T27097372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sidi Maarouf |
E686341
|
entity |
| Predicate | hasMountainousCharacteristics |
P45689
|
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: [Sidi Maarouf, hasMountainousCharacteristics, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMountainousCharacteristics Context triple: [Sidi Maarouf, hasMountainousCharacteristics, true]
-
A.
hasMountainousTerrain
chosen
Indicates that a location or area possesses predominantly mountainous physical terrain or landscape features.
-
B.
hasMountain
Indicates that a location or region possesses or contains at least one mountain.
-
C.
hasMountainScenery
Indicates that a place or area features views or landscapes dominated by mountains.
-
D.
hasMajorMountainRange
Indicates that one entity possesses, contains, or is geographically associated with a principal or significant mountain range.
-
E.
hasMountainRange
Indicates that one entity possesses, contains, or is geographically associated with a specific mountain range.
- 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_69ef1489f8b481908e24a1985982bd26 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f7221dc9a88190bb8194fcc29c42bc |
completed | May 3, 2026, 10:23 a.m. |
| PD | Predicate disambiguation | batch_69f72153a9188190b02adc84e1be4af8 |
completed | May 3, 2026, 10:20 a.m. |
Created at: April 27, 2026, 8:45 a.m.